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Thesis & Dissertation Acknowledgements | Tips & Examples

Published on May 3, 2022 by Tegan George . Revised on July 18, 2023.

The acknowledgements section is your opportunity to thank those who have helped and supported you personally and professionally during your thesis or dissertation process.

Thesis or dissertation acknowledgements appear between your title page and abstract  and should be no longer than one page.

In your acknowledgements, it’s okay to use a more informal style than is usually permitted in academic writing , as well as first-person pronouns . Acknowledgements are not considered part of the academic work itself, but rather your chance to write something more personal.

To get started, download our step-by-step template in the format of your choice below. We’ve also included sample sentence starters to help you construct your acknowledgments section from scratch.

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Table of contents

Who to thank in your acknowledgements, how to write acknowledgements, acknowledgements section example, acknowledgements dos and don’ts, other interesting articles, frequently asked questions about the acknowledgements section.

Generally, there are two main categories of acknowledgements: professional and personal .

A good first step is to check your university’s guidelines, as they may have rules or preferences about the order, phrasing, or layout of acknowledgements. Some institutions prefer that you keep your acknowledgements strictly professional.

Regardless, it’s usually a good idea to place professional acknowledgements first, followed by any personal ones. You can then proceed by ranking who you’d like to thank from most formal to least.

• Chairs, supervisors, or defense committees
• Funding bodies
• Other academics (e.g., colleagues or cohort members)
• Editors or proofreaders
• Librarians, research/laboratory assistants, or study participants
• Family, friends, or pets

Typically, it’s only necessary to mention people who directly supported you during your thesis or dissertation. However, if you feel that someone like a high school physics teacher was a great inspiration on the path to your current research, feel free to include them as well.

Professional acknowledgements

It is crucial to avoid overlooking anyone who helped you professionally as you completed your thesis or dissertation. As a rule of thumb, anyone who directly contributed to your research process, from figuring out your dissertation topic to your final proofread, should be mentioned.

A few things to keep in mind include:

• Even if you feel your chair didn’t help you very much, you should still thank them first to avoid looking like you’re snubbing them.
• Be sure to follow academic conventions, using full names with titles where appropriate.
• If several members of a group or organization assisted you, mention the collective name only.
• Remember the ethical considerations around anonymized data. If you wish to protect someone’s privacy, use only their first name or a generic identifier (such as “the interviewees”)/

Personal acknowledgements

There is no need to mention every member of your family or friend group. However, if someone was particularly inspiring or supportive, you may wish to mention them specifically. Many people choose to thank parents, partners, children, friends, and even pets, but you can mention anyone who offered moral support or encouragement, or helped you in a tangible or intangible way.

Some students may wish to dedicate their dissertation to a deceased influential person in their personal life. In this case, it’s okay to mention them first, before any professional acknowledgements.

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After you’ve compiled a list of who you’d like to thank, you can then sort your list into rank order. Separate everyone you listed into “major thanks,” “big thanks,” and “minor thanks” categories.

• “Major thanks” are given to people who your project would be impossible without. These are often predominantly professional acknowledgements, such as your advisor, chair, and committee, as well as any funders.
• “Big thanks” are an in-between, for those who helped you along the way or helped you grow intellectually, such as classmates, peers, or librarians.
• “Minor thanks” can be a catch-all for everyone else, especially those who offered moral support or encouragement. This can include personal acknowledgements, such as parents, partners, children, friends, or even pets.

How to phrase your acknowledgements

To avoid acknowledgements that sound repetitive or dull, consider changing up your phrasing. Here are some examples of common sentence starters you can use for each category.

Note that you do not need to write any sort of conclusion or summary at the end. You can simply end the acknowledgements with your last thank you.

Here’s an example of how you can combine the different sentences to write your acknowledgements.

A simple construction consists of a sentence starter (in purple highlight ), followed by the person or entity mentioned (in green highlight ), followed by what you’re thanking them for (in yellow highlight .)

Acknowledgements

Words cannot express my gratitude to my professor and chair of my committee for her invaluable patience and feedback. I also could not have undertaken this journey without my defense committee, who generously provided knowledge and expertise. Additionally, this endeavor would not have been possible without the generous support from the MacArthur Foundation, who financed my research .

I am also grateful to my classmates and cohort members, especially my office mates, for their editing help, late-night feedback sessions, and moral support. Thanks should also go to the librarians, research assistants, and study participants from the university, who impacted and inspired me.

Lastly, I would be remiss in not mentioning my family, especially my parents, spouse, and children. Their belief in me has kept my spirits and motivation high during this process. I would also like to thank my cat for all the entertainment and emotional support.

• Write in first-person, professional language
• Thank your professional contacts first
• Include full names, titles, and roles of professional acknowledgements
• Include personal or intangible supporters, like friends, family, or even pets
• Mention funding bodies and what they funded
• Appropriately anonymize or group research participants or non-individual acknowledgments

Don’t:

• Use informal language or slang
• Go over one page in length
• Mention people who had only a peripheral or minor impact on your work

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In the acknowledgements of your thesis or dissertation, you should first thank those who helped you academically or professionally, such as your supervisor, funders, and other academics.

Then you can include personal thanks to friends, family members, or anyone else who supported you during the process.

Yes, it’s important to thank your supervisor(s) in the acknowledgements section of your thesis or dissertation .

Even if you feel your supervisor did not contribute greatly to the final product, you must acknowledge them, if only for a very brief thank you. If you do not include your supervisor, it may be seen as a snub.

The acknowledgements are generally included at the very beginning of your thesis , directly after the title page and before the abstract .

In a thesis or dissertation, the acknowledgements should usually be no longer than one page. There is no minimum length.

You may acknowledge God in your dissertation acknowledgements , but be sure to follow academic convention by also thanking the members of academia, as well as family, colleagues, and friends who helped you.

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Acknowledgement in Research Paper – A Quick Guide [5 Examples]

The acknowledgement section in your research paper is where you thank those who have helped or supported you throughout your research and writing. It is a short section of 3-5 paragraphs or no more than 300 words you put on a page after the title page.

Saying thank you with style

How to write an acknowledgement: the complete guide for students, why should i include an acknowledgement in my research paper.

Acknowledging assistance and contributions from others can establish your integrity as a researcher. This will eventually make your work more credible.

What should be acknowledged about (aka thankful for)?

Who should be included in the acknowledgement of a research paper.

You can include everyone who helped you technically, intellectually, or financially (assistance with grants or monetary help) in the process of researching and writing your research paper. Except for your family and friends, you should always include the full names with the title of these individuals:

You can start with your professor or the individuals who supported you the most throughout the research. And then you can continue by thanking your institution and then the reviewer who reviewed your paper. Then you can thank your friends and families and any other individual who helped.

What is the tone of the acknowledgement in a research paper?

You should write your acknowledgement in formal language with complete sentences. It is appropriate to write in the first person (‘I’ for a single author or ‘we’ for two or more).

Writing an acknowledgement for research paper is one of the important parts of your project report. You need to thank everyone for  helping you with your paper . Here are some examples of acknowledgement for your research paper.

Acknowledgement in Research Paper: Example 1

Acknowledgement in research paper: example 2, acknowledgement in research paper: example 3, acknowledgement in research paper: example 4, acknowledgement in research paper: example 5.

You can use these or try to create your own version for your project report. Also, you can use our auto  acknowledgement generator tool  to automatically generate acknowledgement for your project.

Where should I put the acknowledgement section?

How long is an acknowledgement in a research paper.

The acknowledgement section (usualy inserted as a page) of your research paper should consist of 3-5 paragraphs or no more than 300 words you put on a page after the title page.

Should I use the full names of family members in an acknowledgement?

You do not necessarily need to use the full name for your family and friends (it would sound pretty awkward to use the full name of your parent or spouse right?), you should always include the full names with the title for all other individuals in your acknowledgement.

Can I use “first person” in an acknowledgement?

What is an acknowledgement in academic writing?

More Definitions on Acknowledgement

“acknowledgement” vs “acknowledgment”… …what the hack.

Both “acknowledgement” and “acknowledgment” are used in the English-speaking world. However, acknowledgement with the “e” in the middle is more commonly used. It is up to 24.5 times more popular in the top 5 English-speaking countries in the world.

Other Popular Acknowledgement Examples

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Acknowledgement Examples for School/College Projects

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Thesis Acknowledgements Examples

5 Examples For Your Inspiration

By: Derek Jansen (MBA) | Reviewers: Dr Eunice Rautenbach | May 2024

The acknowledgements section of your thesis or dissertation is an opportunity to say thanks to all the people who helped you along your research journey. In this post, we’ll share five thesis acknowledgement examples to provide you with some inspiration.

Overview: Acknowledgements Examples

• The acknowledgements 101
• Example:  Formal and professional
• Example:  Warm and personal
• Example:  Challenge-centric
• Example:  Institution-centric
• Example:  Reflective and philosophical
• FREE Acknowledgements template

Acknowledgements 101: The Basics

The acknowledgements section in your thesis or dissertation is where you express gratitude to those who helped bring your project to fruition. This section is typically brief (a page or less) and less formal, but it’s crucial to thank the right individuals in the right order .

As a rule of thumb, you’ll usually begin with academic support : your supervisors, advisors, and faculty members. Next, you’ll acknowledge any funding bodies or sponsors that supported your research. You’ll then follow this with your intellectual contributors , such as colleagues and peers. Lastly, you’ll typically thank your personal support network , including family, friends, and even pets who offered emotional support during your studies.

As you can probably see, this order moves from the most formal acknowledgements to the least . Typically, your supervisor is mentioned first, due to their significant role in guiding and potentially evaluating your work. However, while this structure is recommended, it’s essential to adapt it based on any specific guidelines from your university. So, be sure to always check (and adhere to) any requirements or norms specific to your university.

With that groundwork laid, let’s look at a few dissertation and thesis acknowledgement examples . If you’d like more, check out our collection of dissertation examples here .

Need a helping hand?

Example #1: Formal and Professional

This acknowledgement formally expresses gratitude to academic mentors and peers, emphasising professional support and academic guidance.

I extend my deepest gratitude to my supervisor, Professor Jane Smith, for her unwavering support and insightful critiques throughout my research journey. Her deep commitment to academic excellence and meticulous attention to detail have significantly shaped this dissertation. I am equally thankful to the members of my thesis committee, Dr. John Doe and Dr. Emily White, for their constructive feedback and essential suggestions that enhanced the quality of my work.

My appreciation also goes to the faculty and staff in the Department of Biology at University College London, whose resources and assistance have been invaluable. I would also like to acknowledge my peers for their camaraderie and the stimulating discussions that inspired me throughout my academic journey. Their collective wisdom and encouragement have been a cornerstone of my research experience.

Finally, my sincere thanks to the technical staff whose expertise in managing laboratory equipment was crucial for my experiments. Their patience and readiness to assist at all times have left a profound impact on the completion of my project.

Example #2: Warm and Personal

This acknowledgement warmly credits the emotional and personal support received from family, friends and an approachable mentor during the research process.

This thesis is a reflection of the unwavering support and boundless love I received from my family and friends during this challenging academic pursuit. I owe an immense debt of gratitude to my parents, who nurtured my curiosity and supported my educational endeavours from the very beginning.

To my partner, Alex, your endless patience and understanding, especially during the most demanding phases of this research, have been my anchor. A heartfelt thank you to my supervisor, Dr. Mark Brown, whose mentorship extended beyond the academic realm into personal guidance, providing comfort and motivation during tough times.

I am also thankful for my friends, who provided both distractions when needed and encouragement when it seemed impossible to continue. The discussions and unwavering support from my peers at the university have enriched my research experience, making this journey not only possible but also enjoyable. Their presence and insights have been pivotal in navigating the complexities of my research topic.

Example #3: Inclusive of Challenges

This acknowledgement recognises the wide range of support received during unexpected personal and academic challenges, highlighting resilience and communal support.

The path to completing this dissertation has been fraught with both professional challenges and personal adversities. I am profoundly grateful for the enduring support of my supervisor, Dr. Lisa Green, whose steadfast belief in my capabilities and academic potential encouraged me to persevere even during my lowest moments. Her guidance was a beacon of light in times of doubt.

I must also express my deepest appreciation for my family, who stepped in not only with emotional reassurance, but also with critical financial support, when unexpected personal challenges arose. Their unconditional love and sacrifice have been the foundation of my resilience and success.

I am thankful, too, for the support services at the university, including the counselling centre, whose staff provided me with the tools to manage stress and maintain focus on my academic goals. Each of these individuals and institutions played a crucial role in my journey, reminding me that the pursuit of knowledge is not a solo expedition but a communal effort.

Example #4: Institution-Centric

This acknowledgement succinctly appreciates the financial, academic, and operational support provided by the university and its staff.

This dissertation would not have been possible without the generous financial support from the University of Edinburgh Scholarship Programme, which enabled me to focus fully on my research without financial burden. I am profoundly grateful to my advisor, Professor Richard Miles, for his sage advice, rigorous academic guidance, and the confidence he instilled in me. His expertise in the field of microbiology greatly enriched my work.

I would also like to thank the staff at the university library, whose assistance was indispensable. Their patience and willingness to help locate rare and essential resources facilitated a thorough and comprehensive literature review. Additionally, the administrative and technical staff, who often go unmentioned, provided necessary support that greatly enhanced my research experience. Their dedication and hard work create an environment conducive to academic success.

Lastly, my peers’ encouragement and the intellectual environment at the university have been vital in completing my research.

Example #5: Reflective and philosophical

This acknowledgement reflects on the philosophical growth and personal insights gained through the support of mentors, peers, and family, framing the dissertation as a journey of intellectual discovery.

Completing this thesis has been not only an academic challenge but also a profound journey of personal and philosophical growth.

I am immensely grateful to my mentor, Professor Sarah Johnson, for encouraging me to explore complex ideas and to challenge conventional wisdom. Her guidance helped me navigate the philosophical underpinnings of my research and deepened my analytical skills. My fellow students in the Philosophy Department provided a supportive and intellectually stimulating community. Our discussions extended beyond the classroom, offering new insights and perspectives that were crucial to my thesis.

I am also deeply thankful for my family, whose intellectual curiosity and spirited philosophical debates at home sparked my interest in philosophy from a young age. Their continuous support and belief in my academic pursuits have been instrumental in my success.

This dissertation reflects not only my work but also the collective support of everyone who has touched my life academically and personally. The journey has taught me the value of questioning and the importance of diverse perspectives in enriching our understanding of complex philosophical issues.

FREE Acknowledgements Template

To help fast-track your writing process, we’ve created a free, fully editable template . This template covers all the necessary content for a generic thesis or dissertation acknowledgements section. If you’re interested, you can download a copy here .

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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How to Write Acknowledgement in Research Paper

Table of Contents

Writing an acknowledgement in a research paper is an integral part of the process. It is a formal way of expressing gratitude to the individuals and institutions that contributed to the completion of your research.

This section, though not mandatory, holds significant value as it acknowledges the efforts of those who assisted you in the successful completion of your project. In this comprehensive guide, we will delve into the intricacies of writing an effective acknowledgement for your research paper.

Introduction

Acknowledgements serve a crucial role in research papers . They not only express gratitude but also provide a sense of credibility to your work. Acknowledging the contributions of others shows that your research is a collective effort, which can enhance the perceived validity of your findings.

Moreover, acknowledgements can also serve as a platform for you to demonstrate your professional courtesy and respect for the individuals and institutions that have supported your research. This can help in fostering positive relationships, which can be beneficial for your future research endeavors.

Who to acknowledge in your research paper ?

Deciding who to acknowledge in your research paper can be a challenging task. It is important to ensure that you do not overlook anyone who has contributed to your research. Here are some categories of individuals and institutions that you might consider acknowledging:

Academic advisors and supervisors:

Your academic advisors and supervisors are likely to be your first point of contact for guidance and support during your research. They provide valuable insights, feedback, and direction, which can significantly influence the outcome of your research.

Therefore, acknowledging them in your research paper is a way of expressing your gratitude for their assistance and guidance. It also shows your respect for their expertise and dedication to your research.

Research participants and collaborators

Research participants and collaborators play a crucial role in the success of your research. They provide the data or information necessary for your research, making their contribution invaluable.

Acknowledging them in your research paper is a way of showing your appreciation for their time and effort. It also symbolizes your respect for their contribution to your research.

Funding bodies and institutions:

Funding bodies and institutions provide the financial support necessary for conducting your research. Without their support, it might be challenging to carry out your research effectively.

Therefore, acknowledging them in your research paper is a way of expressing your gratitude for their financial support. It also shows your appreciation for their trust in your research capabilities.

How to write acknowledgements for your research paper?

Writing acknowledgements for your research paper involves more than simply listing names. It requires a thoughtful and sincere expression of gratitude. Here are some steps to guide you in writing effective acknowledgements:

Start with the most significant contributions:

Begin your acknowledgements by expressing gratitude to those who have made the most significant contributions to your research. This could be your academic advisors, supervisors, or funding bodies. Starting with the most significant contributions helps to set the tone for the rest of your acknowledgements.

Ensure that you express your gratitude sincerely and professionally. Avoid using overly emotional or informal language as this can undermine the professionalism of your acknowledgements.

Acknowledge other contributors:

After acknowledging the most significant contributors, proceed to acknowledge other individuals and institutions that have supported your research. This could include research participants, collaborators, and other supportive individuals or institutions.

When acknowledging these contributors, be sure to express your gratitude sincerely and professionally. Also, ensure that you acknowledge each contributor individually to show your appreciation for their unique contribution.

Use appropriate language and tone:

The language and tone you use in your acknowledgements can significantly influence how they are perceived. Therefore, it is important to use appropriate language and maintain a professional tone throughout your acknowledgements.

Use formal language and avoid using jargon or colloquial expressions. Also, maintain a consistent tone throughout your acknowledgements to ensure that they are coherent and easy to read.

Examples of acknowledgements in research papers

Here are a few examples that demonstrate how to acknowledge different contributors effectively:

"I would like to express my deepest gratitude to my advisor, Professor ABC, for his invaluable guidance and support throughout this research. His expertise and dedication have been a source of inspiration and motivation."

Research participants and collaborators:

"I am deeply grateful to all the participants who generously shared their time and experiences for this research. Their contributions have been instrumental in the success of this study."

"This research was made possible by the generous funding from ABC Foundation. I am profoundly grateful for their support and trust in my research capabilities."

Writing acknowledgements in a research paper is a thoughtful process that requires careful consideration of who to acknowledge and how to express gratitude. By following the guidelines and examples provided in this article, you can write effective acknowledgements that reflect your appreciation and respect for the contributions of others to your research.

Remember, acknowledgements are more than just a formality. They are an opportunity to express your gratitude and respect for the individuals and institutions that have supported your research journey. So, take the time to write acknowledgements that are sincere, professional, and reflective of your gratitude.

Frequently Asked Questions

In a research paper, the acknowledgment section is where the author shows appreciation to those who helped with the research. It's usually found at the start of the paper, before the main text begins. However, the exact location varies depending on the university guidelines.

Citations are formal ways to acknowledge the sources you used, while acknowledgments are more personal and can serve as a confidential way to thank someone for their help or contribution.

The purpose of including acknowledgement is to express gratitude to everyone who assisted with the research but didn't meet the criteria for being listed as an author.

There is no minimum length for writing an acknowledgement in a research paper but it should not be more than one page.

If you conducted the research entirely by yourself and received no assistance or support from others, it's not necessary to include acknowledgements. However, if you received any form of support or assistance, even if minimal, it's appropriate to acknowledge it.

Yes, it's appropriate to acknowledge funding sources in your research.

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Dissertation acknowledgments [with examples]

What are dissertation acknowledgements?

What to consider when writing your dissertation acknowledgments, who to thank in your dissertation acknowledgments, what (and what not) to write in your dissertation acknowledgments, good examples of dissertation acknowledgments, a final word on writing dissertation acknowledgments: have fun, frequently asked questions about dissertation acknowledgments, related articles.

While you may be the sole author of your dissertation, there are lots of people who help you through the process—from your formal dissertation advisors to the friends who may have cooked meals so that you could finish your last chapter . Dissertation acknowledgments are a chance to thank everyone who had a hand in the completion of your project.

Dissertation acknowledgments are a brief statement of your gratitude to advisors, professors, peers, family, and friends for their help and expertise.

In this guide, we’ll cover:

• the most important things to consider when you’re writing your dissertation acknowledgments
• who to thank in your dissertation acknowledgments
• what (and what not) to write in your dissertation acknowledgments
• short examples of dissertation acknowledgments

Once you’re at the stage where you’re writing your dissertation acknowledgments, you may be tempted to kick back and relax. After all, the hard part of writing the dissertation itself is over and a list of thanks should be simple to churn out.

However, the acknowledgments are an important part of your overall work and are something that most people who read your dissertation, including prospective employers, will look at.

Tip: The best dissertation acknowledgements are concise, sincere, and memorable.

Approach this part of the process, brief as it may be compared to the long haul of writing the dissertation, with the same high level of care and attention to detail. It’s an explicit and permanent statement of who made a real impact on your work and contributed to your academic success.

Plus, the people you thank are often deeply moved by being included—some even go so far as to frame the acknowledgments. Aim to make yours sincere, memorable and something that people will be touched by.

First things first: who should you include in your dissertation acknowledgments? If you’re not sure who to thank, try the brainstorming technique to generate some ideas. Consider these two approaches:

• Make a list of everyone, both professional and personal, who was involved at any point during your work on your dissertation, and then thin down the list from there.
• Make a list of the pivotal aspects of your process and think about who was involved and how they helped.

As you select the people and groups to include in your dissertation acknowledgments, keep in mind that it’s essential to acknowledge your supervisor and anyone else with a visible connection to your work.

It’s an unfortunate reality that not every supervisor goes above and beyond to provide feedback and guidance to the students they are supposed to supervise. However, leaving them out, even if you personally felt disappointed by their involvement or lack thereof, could be seen as a snub.

You should end up with a fairly short list of people to thank. While being mindful of professional etiquette and personal feelings, be choosy about who makes the final cut since your acknowledgments should be limited to no more than a page.

Now that you have your list of people and groups to thank, it’s time to start writing. Before your first pen or keystroke, however, check your university’s guidelines as your institution may have specific rules around what can and cannot be included.

The standard practice is to begin with the formal and then progress to the informal, so the first people to mention would be:

• supervisors
• committee members
• other professional contacts

Use their full names and titles and go into brief detail about how they contributed to your work.

Once those are done, you can move on to the personal thanks, which can include friends, family, even pets. If you are so inclined, it is also considered appropriate to thank God or make mention of spiritual support.

You may also choose to inject a little humor at this point, but don’t get carried away and definitely don’t include sarcasm or critical comments of any kind, including self-critical ones. Remember that the acknowledgments precede your dissertation, so you want to be taken seriously.

A couple more basics that are essential when creating your acknowledgments:

• Position: Acknowledgments should be placed after the title page and before the abstract.
• Perspective: Write from the first-person perspective and speak in your own voice.

A really good way to get a sense of how to write your own dissertation acknowledgments is to read ones written by others. Notice which ones you respond particularly well to and use them as a model upon which to base your own.

Here are some good examples to help you get started:

I couldn’t have reached this goal without the help of many people in my life. I’d like to take this opportunity to thank them for their support.

First, my sincere thanks to my dissertation committee. The value of their guidance cannot be overstated. Dr. Elaine Gooding and Dr. Matthew Hunter provided much wisdom that helped me chart my course. I couldn’t have asked for a better supervisor than Dr. Fiona Moore, whose knowledge and experience guided me every step of the way.

Next, I’d like to thank my partner, Elliott. Your votes of confidence kept me going when my spirits dipped. I couldn’t have done this without you.

Last but not least, I’d like to acknowledge the emotional support provided by my family and friends. We made it to the top of the mountain! I look forward to celebrating with all of you.

This example is shorter, but still contains the key components:

Several people played a decisive role in my success and I would like to take this opportunity to thank them.

My chair, Dr. Ronald Saulk, provided invaluable support and infinite patience and I am truly grateful for all of his wisdom and guidance. I also owe the entire staff of the Wilhelm Library a debt of gratitude. From tracking down books and arranging for interlibrary loans to keeping the coffee maker in the lobby well-stocked and in good working order, they offered the practical help and kind gestures that made all the difference.

I’d also like to thank my family and God, for always being there for me.

One final piece of advice: enjoy this process. Writing a dissertation doesn’t happen every day, and the opportunity to acknowledge the important people in your life in a published format is as rare as it is wonderful.

What’s more, this part of your dissertation is unlike any other. It’s unbounded by the conventions that apply to the formal work. It’s a chance to really flex some creative muscle and let your personality shine through. So make the most of it and have fun!

In your dissertation acknowledgments, you thank everyone who has contributed to your work or supported you along the way. Who you want to thank is a very personal choice, but you should include your supervisors and anyone else with a visible connection to your work. You may also thank friends, family, and partners.

First, you need to come up with a list of people you want to thank in your dissertation acknowledgments. As a next step, begin with the formal and then progress to the informal, so the first people to mention would be supervisors, mentors, committees, and other professional contacts. Then, you can move on to the personal thanks, which can include friends, family, even pets.

Who you acknowledge in your dissertation is ultimately up to you. You should, however, thank your supervisor and anyone else with a visible connection to your work. Leaving them out, even if you personally felt disappointed by their involvement or lack thereof, could be seen as a snub. In addition, you can thank friends, partners or family.

There are many ways so you can acknowledge your dissertation supervisor. Some examples can be found in this article above. If you need more examples, you can find them here .

While acknowledgments are usually more present in academic theses, they can also be a part of research papers. In academic theses, acknowledgments are usually found at the beginning, somewhere between abstract and introduction. In research papers, acknowledgments are usually found at the end of the paper.

How to write a unique thesis acknowledgement (+ FAQs)

Crafting a thesis acknowledgement is typically one of the final steps in completing a thesis. This post aims to assist you in gaining insights and guidance by addressing common questions related to thesis acknowledgements. By doing so, it enables you to create a distinct and meaningful acknowledgment section that reflects your gratitude and appreciation.

What is a thesis acknowledgement?

Do i need a thesis acknowledgement.

While a thesis acknowledgement is typically not a mandatory requirement, omitting it might not be seen positively. Writing a thesis almost always involves some form of assistance or support, whether from a supervisor, family, or friends.

Acknowledging these contributions is not only considerate but also showcases your gratitude and reflects well on your character. Including a thesis acknowledgement demonstrates your appreciation for the help you received throughout your academic journey, underscoring the collaborative nature of research and academic pursuits.

Who should I thank in my thesis acknowledgment?

The thesis acknowledgement offers flexibility, but thanking your thesis supervisor/s is an absolute must—non-negotiable. It would be highly unusual to omit their appreciation.

Apart from these essentials, you have the freedom to thank anyone you desire. Common mentions include parents, partners, friends, peers, and colleagues. Some may even extend gratitude to pets or coffee! Injecting humor is acceptable, but maintaining a certain level of formality is advised, as explained in the subsequent section.

How to deal with a thesis supervisor with whom I had a challenging relationship in my thesis acknowledgement?

When doing so, maintain a concise approach while ensuring a respectful and diplomatic tone, refraining from any negative aspects or conflicts. Instead, emphasize the professional aspects of their contribution, such as supporting the development of the theoretical framework or providing valuable critical feedback that enhanced the quality of your work.

How can I make my thesis acknowledgement uniquely personal?

Once you have decided whom to thank in your thesis acknowledgement, consider going beyond generic expressions of gratitude. Making your acknowledgements more personal and specific can make them truly special. Instead of simply thanking someone for their guidance and support, include examples that highlight the unique contributions of those individuals.

For instance, if you are thanking your fellow thesis writers, you can say something like: “Long study sessions at the library with John and Sabine made thesis writing a joyful experience.” This demonstrates the specific way they contributed to your journey.

By providing concrete examples, your acknowledgements become more heartfelt and memorable, showing the genuine impact of each person you thank.

How formal should a thesis acknowledgement be?

While there are no strict rules for writing a thesis acknowledgement, it’s essential to consider its significance as one of the first things readers encounter in your thesis. Therefore, maintaining a certain level of formality is advised.

Remember that your thesis is an academic work, and the acknowledgement should not detract from its academic merit. Focus on expressing gratitude to those who contributed to your academic journey in a professional and appropriate manner.

To what extent should I express personal sentiments in my thesis acknowledgement?

And of course make sure that the information you reveal about the people you thank, they are also comfortable with it. You should not, for instance, describe your messy breakup with a person and even worse naming the person by name. Instead, you can write something more neutral in a way that people who know you well still know what you mean. For instance, you could thank your friends for always being there for you during challenging times, which you are grateful for.

How should I structure my thesis acknowledgement?

When writing a thesis acknowledgement, there are several acceptable ways to structure it, each serving its purpose. Three commonly used approaches stand out.

The second approach involves structuring the acknowledgement based on the nature of relationships, ranging from formal to personal. Here, you begin by expressing thanks to your formal supervisors and professors who played a significant role in shaping your research, then move on to more informal yet professional mentors. Subsequently, you extend your gratitude to friends, family, and, if applicable, your partner or spouse.

How long should a thesis acknowledgement be?

For bachelor or master theses, the average length typically ranges from 100 to 250 words, equivalent to about half a page.

Where is the thesis acknowledgement located?

When formatting your document, it’s advisable to insert blank pages to maintain a proper layout in the printed version, especially when double-paged printing is used. To achieve this layout, page 1 is reserved for the title page, page 2 is often left empty, and page 3 contains the thesis acknowledgement. Additionally, page four is frequently left blank as well. This arrangement enhances the reading experience of the printed version and provides a more polished appearance to the document.

Where can I find examples of thesis acknowledgements?

In addition to utilizing the university’s repository, I have created five examples of PhD thesis acknowledgements that you can review for further guidance and ideas.

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Thesis acknowledgements: Samples and how to write your own thesis or dissertation acknowledgements

Writing a thesis can be tricky. That’s why I’m starting a new series covering each section of the thesis, from thesis acknowledgements all the way to conclusions. I’ll be guiding you through the whole process, from what to include in your thesis to how to write it, along with examples from defended theses to help you to write your own.

We’ll begin by covering thesis acknowledgments. The acknowledgements section appears at the start of the thesis so it is often one of the first parts that everyone tries to tackle. As this will likely be your first taste of your thesis it can often feel quite intimidating to write!

Thankfully it’s also one of the easiest parts of the thesis to complete, which may help to give you a boost for the rest.

In this post we’ll cover everything to do with thesis acknowledgements: samples, what to include and how to write them. At the end I’ll also outline a 60 minute exercise which will get you preparing a first draft of your own! I’ve also got a similar post to craft your thesis title, which you can check out here .

I’m writing this post with a PhD thesis in mind but it could work just as well if you’re looking for help including acknowledgements in your Master’s or undergraduate thesis/ dissertation.

What is the purpose of the acknowledgements section in a thesis?

The acknowledgements section of your thesis is an opportunity to reflect on the people who have supported and shaped your PhD experience.

Don’t worry, although your examiners will be interested to read your acknowledgements section, you won’t really get judged on it in your PhD viva. This section is for you to share as little, or as much, as you want about everyone involved in your PhD journey.

The acknowledgements are a very personal section of your thesis and each PhD student will have different things they want to include. For example, many people wonder: How do I thank my family in a thesis? And the acknowledgements section is the answer!

Note – You can also use a thesis dedication to thank your family. This is a separate section to your thesis acknowledgements and is entirely optional. It’s usually just a single line, just like you might find at the front of some books. Most people don’t include a separate dedication section but you can if you want to go that extra step.

What to include in your thesis acknowledgements

There are usually no formal requirements dictating what to include in your acknowledgements. However, do double check for any potential rules at your specific institution.

In general the acknowledgements are the section of your thesis where you have some creative liberty and are not bound by rigid research protocols or guidelines.

Many students choose to use the acknowledgements section to thank people (or organisations) who:

• Introduced them to the topic
• Helped with their PhD application
• Funded the project
• Supervisors
• Technicians
• Partners, friends or family
• Or anyone else who made an impression along the way!

But remember, you can include whatever you want! For example in my own PhD acknowledgements, which you’ll read further down this post, I thanked the university for providing a green outdoor space for us.

Acknowledge whoever and whatever influenced your own PhD experience.

You may find it helpful to start by writing a list of everyone you wish to thank.

How do you write an acknowledgements section?

Since there are no guidelines to worry about, it is really up to you how you write your own thesis acknowledgements. You have a lot of freedom for what to include and how to write it.

However you may find the following suggested phases helpful as a starting point.

Who you want to thank…

• “First and foremost, I would like to express my sincere gratitude to…”
• “I must thank…”
• “A special thanks to…”
• “I would like to highlight two truly exceptional people from…”
• “I want to thank…”
• “In addition, I would like to mention”
• “I would also like to extend my thanks to…”
• “I want to give my deepest appreciation to…”
• “Finally, but the most importantly, I would like to thank…”

…then, why you want to thank them

It can be nice to also include why you’re thanking these people, using phrases such as:

• “…for the opportunity to be a part of this project”
• “…for always being there when I needed his support, reviewing my progress constantly, and guiding me through my PhD studies”
• “….for being a great bunch of people in and out of the lab”
• …”for all the guidance, support and outstanding feedback”
• “… who took their time to help teach me…”
• “…for her unlimited support and unconditional guidance during my PhD journey”
• “…were always there for discussions about anything that I was unsure on”
• “…whom has offered invaluable advice that will benefit me throughout my life”
• “…for supporting me since my undergraduate, and for the valuable discussions we had along the road”
• “…for making the past 4 years much more enjoyable and keeping me sane throughout the whole process”

Here is a whole example from an accepted PhD thesis:

Firstly, I want to thank [supervisor’s name(s)] for giving me the opportunity to work on this project, providing valuable guidance and feedback, and challenging me to grow as a scientist.  Excerpt from Dr Wane’s thesis acknowledgements, available via this page or use this direct download link .

Some people will choose to use full names and titles for any professional acknowledgements and first names for any personal ones. Again, this is up to you.

To help illustrate the variety of thesis acknowledgement formats, we’ll shortly be coming on to some examples of acknowledgment sections from successfully defended theses.

Before then I want to cover some of the main questions relating to how to write your own thesis acknowledgements section:

How long should you spend writing your thesis acknowledgements?

My suggestion is to spend only an hour or two making a first draft. I suggest doing this well ahead of your final deadline so that you have time to come back to it. Even so, I’d certainly look to spend far less than one day’s work on it in total.

It is a “nice to have” and means a lot to a lot of people, but remember you’re really only writing this section for yourself. I probably spent about two hours writing mine in total, simply because it wasn’t a priority for me.

What order should you write your acknowledgements in?

A typical way to write your acknowledgements is to go from the most formal/academic relationships to the least.

It is normal to start with any funding bodies, then formal people like your PhD supervisors, then move through labmates, friends and family. But again, there are generally no rules!

How long should the acknowledgements section be?

You can include as much or as little as you want. My own PhD acknowledgements section was just under a page long and it consisted of 386 words or 1892 characters (without spaces).

Here is how it was formatted:

But let’s not just look at my thesis. Using Imperial’s publicly accessible database I went through 25 published PhD theses for you.

The average (mean) length of these 25 theses was 365 words and 1793 characters without spaces. Writing an acknowledgements section of length 350-450 words was the most common:

The shortest acknowledgements sections was 122 words(653 characters) long. The longest one consisted of 1022 words and 5082 characters. Hopefully this illustrates that you’re not really bound by any limits. Write as much or as little as you want for this section.

Sample thesis acknowledgements

My own phd thesis acknowledgement.

My own PhD thesis is available here *, the acknowledgements section is on page 5. Here is the complete version of my acknowledgements section:

I would like to acknowledge both EPSRC and the Class of 1964 Scholarship for their financial support. It has been an honour to be the inaugural recipient of the Class of 1964 Scholarship and I am indebted to the donors in providing me complete academic freedom in this research. An immense thank you to my PhD supervisors: Jonathan Jeffers, Ulrich Hansen and Julian Jones. Support and guidance throughout the project from you all has been invaluable. JJ in particular you’ve been a fantastic primary supervisor. Thank you to all the academics who helped me get to this stage. The late Dr Kajal Mallick and his Biomedical Materials course at the University of Warwick was a huge influence and without which I would have never followed this path. My “pre-doc” supervisors in Dr Helen Lee of University of Cambridge and in particular the remarkable Prof Judith Hall OBE of Cardiff University from whom I learned so much. Thanks to Alison Paul and Michael Lim for being so supportive when I was considering applying for PhDs. It has been an amazing experience working between two research groups across different departments, thanks to everyone from the Biomechanics and JRJ groups I’ve worked with and from whom I’ve learned so much. Thank you of course to the Hybrids team I’ve worked so closely on this project with: Fra, Gloria, Agathe, Maria, Silvia, it’s been great fun working with you all! Gloria in particular thanks for you all your help, support and friendship: your inclusivity is appreciated by many. Saman, I’ve been so pleased to have you working on DVC with me and being able to discuss ideas with you really has been invaluable. I am grateful to everyone I’ve collaborated with externally: Farah, Amin and Brett (Natural History Museum) plus Andy and Behzad (Royal Veterinary College), thank you all for your support and input. Thanks also to everyone I’ve met through the Environmental Society at Imperial in particular Chelcie: your friendship and support have added a lot to my life. Thanks to Imperial for providing space for the ESoc garden, taking a break and enjoy nature in this space has certainly improved my work. Thanks of course to my family for their support. Finally, thank you Jo for always being so supportive and helping me every step of the way. My PhD thesis, available here . Acknowledgements are on page 5.

*For me the thesis was a means to an end. I wanted my PhD and didn’t want to spend too long agonising over each page. Therefore, it is possible there are typos in there, if you read any of it: firstly well done, I haven’t looked at it much since submitting the final copy, secondly, please don’t tell me about any typos you find!

Other PhD thesis acknowledgement examples

Below are the other 24 published and openly accessible STEM PhD theses I found for this article.

For each person’s thesis, either follow the first link to be taken to the landing page or follow the second link to directly download their thesis: I gave you a choice in case you don’t want stuff to start downloading automatically from a random text link!

The list is formatted as follows:

• [Link to thesis page on repository], [which page the acknowledgements appear on], [direct link to download the thesis]
• Dr Shipman’s thesis , for the acknowledgements go to page 3. Direct download here .
• Longest acknowledgements section of the list at 1022 words.
• Dr Li’s thesis , page 11. Direct download here .
• Dr Podgurschi’s thesis , page 5. Direct download here .
• Dr Medjeral-Thomas’ thesis page 3. Direct download here .
• Dr Sztuc’s thesis , page 5. Direct download here .
• Dr Yap’s thesis , page 5. Direct download here .
• Dr Sukkar’s thesis , page 9. Direct download here .
• Dr Lo’s thesis , page 11. Direct download here .
• Dr Sullivan’s thesis , page 5. Direct download here .
• Dr Tawy’s thesis , page 3. Direct download here .
• Dr Wane’s thesis , page 2. Direct download here .
• Dr Addison’s thesis , page 4. Direct download here .
• Dr Wang’s thesis , page 5. Direct download here .
• Dr Sebest’s thesis , page 3. Direct download here .
• Dr Hopkins’ thesis , page 7. Direct download here .
• Dr Bates’s thesis , page 4. Direct download here .
• Dr Somuyiwa’s thesis , page 6. Direct download here .
• Dr Reynolds’ thesis , page 5. Direct download here .
• My labmate’s thesis, who wrote the acknowledgements in a different style to the rest by using bullet points.
• Shortest acknowledgements section of the list at 122 words.
• Dr Manca’s thesis , acknowledgements on page 5. Direct download here .
• Dr Liu’s thesis , page 5. Direct download here .
• Dr Hotinli’s thesis , page 7. Direct download here .

My top tips for writing your own thesis acknowledgements

• Don’t spend too long on them. The acknowledgements section is really not worth spending too much time on. Even worse, since they appear at the start of your thesis, it is tempting to write your acknowledgements first. This can be fine, or, it can be an opportunity for lots of unnecessary procrastination. Which I why I instead suggest that you…
• Write your acknowledgements at the end of your first draft of the thesis. There is no need to write your thesis in the order it is presented. If you write your acknowledgements at the end you’ll be less likely to spend precious time on a section which really doesn’t warrant too much brain power.
• Don’t stress about it. The acknowledgements are merely for yourself and for anyone close to you that you want to thank. There are far more important sections for you to be particular about!
• Remember: You can make changes after you submit the copy for your viva. As with everything in your thesis, you can make changes after you submit the thesis for your viva. The real “final” copy is when you submit your thesis to the university for archiving. Which is even more reason to not spend too much time writing it the first time around.

Draft your own thesis or dissertation acknowledgements in 60 minutes

Hopefully you now feel inspired to start writing your own thesis acknowledgments!

For the exercise below I’d suggest setting a stop-watch on your phone and move on to the next section when the alarm goes, even if you’ve not fully finished. The aim is to have a rough draft at the end which you can polish off at a later point in time.

• Read a few of the example thesis acknowledgements above to get a feel for the structure ( 15 mins )
• List everyone (or everything!) you wish to thank – including any personal and professional acknowledgements in addition to funding bodies if relevant ( 10 mins )
• Decide on a rough order in which to thank them ( 5 mins )
• Craft some sentences using the phrases mentioned above ( 30 mins )

Congratulations you’re now well on your way to having one section of your PhD thesis completed!

I hope this post has been useful for constructing your own thesis or dissertation acknowledgements. It is the first in a series of posts aiming to help your thesis writing by delving into each section in depth. Be sure to let me know if you have any questions or suggestions for other content which you would find useful.

Subscribe below to stay updated about future posts in the series:

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Acknowledgements Example for an Academic Research Paper

Posted by Rene Tetzner | Sep 1, 2021 | How To Get Published | 0 |

Acknowledgements Example for an Academic or Scientific Research Paper This example of acknowledgements for a research paper is designed to demonstrate how intellectual, financial and other research contributions should be formally acknowledged in academic and scientific writing. As brief acknowledgements for a research paper, the example gathers contributions of different kinds – intellectual assistance, financial support, image credits etc. – into a single Acknowledgements section. Do note, however, that the formats preferred by some scholarly journals require the separation of certain contributions such as financial support of research into their own sections.

Although authors often write acknowledgements hastily, the Acknowledgements section is an important part of a research paper. Acknowledging assistance and contributions establishes your integrity as a researcher as well as your connections and collaborations. It can also help your readers with their own research, affect the influence and impact of the researchers and other professionals you thank, and demonstrate the value and purpose of the agencies that fund your work. The contents of the example I have prepared here are appropriate for a research paper intended for publication in a peer-reviewed journal, but the author, the research project, the manuscript studied, the journal publishing the paper and all those to whom gratitude is extended are entirely fictional. They were created for the purpose of demonstrating the following key concerns when writing the acknowledgements for a formal research paper:

•   Writing in the first person (‘I’ for a single author or ‘we’ for two or more) to offer concise but sincere acknowledgements of specific contributions to your research. •   Maintaining formal language, complete sentences and a professional tone to give specific and thorough information about contributions and convey collegial gratitude. •   Expressing respect and appreciation in an appropriate fashion for each and every contribution and avoiding artificial or excessive flattery. •   Using the complete names and preferred name formats for individuals, funding agencies, libraries, businesses and other organisations. Here, for example, I posit that the library holding the relevant manuscript has indicated that the name of the collection (lengthy though it is) should not be abbreviated. •   Acknowledging contributions to your research and paper in the order that best represents the nature and importance of those contributions. The assistance of the author’s mentor comes first here, for instance, whereas the language editor is acknowledged much further down the list. •   Meeting the requirements for acknowledgements set by the journal or other publisher of the research paper. For the example below, the goal is to record all relevant contributions to the research and paper in a single brief Acknowledgements section of 500 words or less – a set of parameters that would suit the acknowledgement requirements or expectations of many academic and scientific journals and even fit into a footnote or endnote if necessary.

Example Acknowledgements for an Academic Research Paper This paper and the research behind it would not have been possible without the exceptional support of my supervisor, Lawrence Magister. His enthusiasm, knowledge and exacting attention to detail have been an inspiration and kept my work on track from my first encounter with the log books of British Naval Ships MS VII.2.77 to the final draft of this paper. Margaret Kempis and Matthew Brown, my colleagues at Western University, have also looked over my transcriptions and answered with unfailing patience numerous questions about the language and hands of British Naval Ships MS VII.2.77. Samantha McKenzie, head librarian of the Southern Region Central Collegiate Library Special Collections and Microfilms Department where British Naval Ships MS VII.2.77 currently resides, not only provided colour images of the manuscript overnight, but unexpectedly shared the invaluable information on the book that she has been gathering for almost twenty years. I am also grateful for the insightful comments offered by the anonymous peer reviewers at Books & Texts. The generosity and expertise of one and all have improved this study in innumerable ways and saved me from many errors; those that inevitably remain are entirely my own responsibility.

Studying British Naval Ships MS VII.2.77 has proved extremely costly and I am most thankful for the Western University Doctoral Fellowship that has provided financial support for the larger project from which this paper grew. A travel grant from the Literary Society of the Southern Region turned the hope of working in person with British Naval Ships MS VII.2.77 into a reality, and the generous offer of free accommodation from Ms McKay (Samantha McKenzie’s aunt) allowed me to continue my research with the book much longer than I could have hoped. The final design of the complicated transcription tables in Appendices I–III is the creative and technical work of Sam Stone at A+AcaSciTables.com, and the language and format of the paper have benefited enormously from the academic editing services of Veronica Perfect. Finally, it is with true pleasure that I acknowledge the contributions of my amazing partner, Kendric James, who has given up many a Friday evening and Sunday afternoon to read every version of this paper and the responses it has generated with a combination of compassion and criticism that only he could muster for what he fondly calls ‘my odd obsession with books about the sea.’

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How to Write an Acknowledgement for a Research Paper

Hey guys, Phill Collins here! Today, I will teach you how to write an acknowledgment section in a research paper. Let’s do this!

Acknowledging contributions is a crucial aspect of creating a thorough research paper. It provides an opportunity to convey appreciation and acknowledge the support from individuals and institutions throughout your work. This piece will explore the intricacies of crafting acknowledgments for papers, offering valuable insights, practical advice, and sample acknowledgments. It aims to assist you in expressing gratitude to those who have played a substantial role in your research journey. As usual, I recommend those of you who struggle with your writings to pay for a research paper to save time and have a stress-free evening.

What Is Acknowledgement in a Research Paper

Acknowledgment in a research paper is a section dedicated to expressing gratitude and recognizing the individuals, institutions, or resources that have contributed to the completion of the research. This section is an opportunity for the author to appreciate the support, guidance, or assistance received during the research process. Acknowledgments go beyond the academic content of the paper and serve as a personal and professional gesture of recognition for those who played a significant role in the research endeavor.

In this section, researchers typically acknowledge the contributions of mentors, advisors, colleagues, or peers who provided valuable insights, feedback, or assistance in shaping the research project. Additionally, institutions, funding agencies, or organizations that supported the research financially or through resources may be acknowledged. The acknowledgment section reflects the collaborative and communal nature of academic work, highlighting the interconnected web of individuals and entities that contribute to the scholarly pursuit.

While there is no strict format for writing acknowledgments, it is important to balance professionalism and sincerity. Authors can use this space to express genuine gratitude, share personal reflections on the collaborative process, and convey the impact of the support received. The acknowledgment section adds a human touch to the paper, recognizing the collective effort that goes into the creation of academic knowledge.

The Role of an Acknowledgment in a Research Papers

The acknowledgment section in a paper plays a vital role in recognizing and appreciating the various contributors and influences that have shaped the research journey. Beyond the academic rigor captured in the main body of the paper, acknowledgments offer a space to express gratitude for the support and guidance received during the research process. This section often serves as a heartfelt acknowledgment of the collaborative effort to bring a research project to fruition.

Essentials of an Acknowledgement in Research Paper

An essential component of a complex paper, the acknowledgment section serves as a heartfelt expression of gratitude towards individuals and entities who have contributed significantly to the research process. In this section, authors typically recognize mentors, advisors, colleagues, and peers who provided valuable insights, guidance, or support. Additionally, institutions, funding sources, or organizations that played a role in the research project are acknowledged. The acknowledgment is a personal touch within the scholarly document, acknowledging the collaborative nature of academic work and underscoring the importance of communal support in the research journey. It adds a human element to the paper, recognizing the interconnected network of individuals and resources that contribute to the scholarly endeavor.

How to Write an Acknowledgement for Research Paper Using 8 Simple Tips

Keep in mind that acknowledgments offer a chance to express gratitude and acknowledge the valuable contributions of those who assisted you. Dedicate time to creating a genuine and thoughtful acknowledgment section that mirrors the collaborative and supportive nature of your research endeavor.

Sincerity and Authenticity

Write your acknowledgments with heartfelt gratitude, conveying genuine appreciation for the support and contributions you received throughout your research journey.

Specific Individuals and Institutions

Identify key figures and entities that played a substantial role in your research, including mentors, advisors, collaborators, and funding agencies. Acknowledge institutions that provided resources or facilities.

Conciseness and Focus

Keep your acknowledgments brief and to the point. Concentrate on highlighting the pivotal individuals and organizations that significantly influenced your research.

Formal Tone

Maintain a professional and formal tone throughout your acknowledgments. Remember that this section serves as a formal recognition of support, not a casual conversation.

Ethical Considerations

Adhere to ethical guidelines and norms when acknowledging individuals and organizations. Respect the privacy and confidentiality of those who may prefer not to be mentioned.

Personal Touches

If appropriate, include personal anecdotes or specific instances where individuals or organizations made a noteworthy impact on your research.

Tailor to Research Context

Consider the nature of your research and customize your acknowledgments accordingly. For instance, if your research is interdisciplinary, recognize experts from various fields who provide valuable insights.

Appreciation Beyond Formal Requirements

While an acknowledgement in research paper has to list individuals and institutions, extend your appreciation to others who indirectly supported you. This may include family, friends, or colleagues who provided emotional support during your research journey.

Example of Acknowledgement in Research Paper

An Additional Example of Acknowledgement in Research Paper

Final Words

In my opinion, acknowledgements in a research paper provide an avenue to convey appreciation and recognize the indispensable contributions of individuals and institutions that have bolstered your work. In this article, I did my best to offer tips and a sample acknowledgment to assist you in authentically expressing your gratitude. Keep in mind that acknowledgments are a chance to genuinely convey appreciation and attribute credit where it is rightfully due.

How to write acknowledgement in research paper?

Begin your acknowledgment section with a formal salutation, expressing gratitude to those who contributed to your research. Use a sincere and appreciative tone, mentioning specific individuals and institutions, and keep it concise.

What is the purpose of the acknowledgement section in a research paper?

The acknowledgment section serves to express gratitude and recognize the contributions of individuals and institutions who supported the research. It reflects the researcher's appreciation for guidance, resources, and collaboration during the project.

What should the acknowledgement section of a research paper include?

An acknowledgement for research paper includes thanks to advisors, committee members, funding agencies, collaborators, institutions providing resources, and anyone who significantly contributed. Maintain a formal tone, adhere to ethical considerations, and, if appropriate, add a personal touch or anecdotes.

How to acknowledge someone in a research paper?

Acknowledge individuals by mentioning their names, roles, and specific contributions. Follow a formal and respectful tone, adhering to ethical guidelines. If applicable, express personal appreciation and consider tailoring acknowledgments to the nature of the research and relationships involved.

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Acknowledgement for Thesis (10 Samples and Writing Tips)

October 22, 2023

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By Mohsin Khurshid

Acknowledging those who contributed to your thesis is a gracious gesture, reflecting your appreciation for their support, both moral and material. This article delves into the art of crafting a meaningful acknowledgment in your thesis, highlighting its importance, and offering valuable samples.

Table of Contents

• 1 Tips on Writing Acknowledgement for Thesis
• 2.1 Acknowledgement Sample for Thesis
• 2.2 Acknowledgement for Thesis Submission
• 2.3 Acknowledgement for Thesis Report
• 2.4 Beautiful Thesis Acknowledgement
• 2.5 Acknowledging God in Thesis
• 2.6 Funny Thesis Acknowledgement
• 2.7 Acknowledgement in Thesis Writing
• 2.8 Thesis Acknowledgement Sample
• 2.9 Example of Acknowledgement in Thesis
• 2.10 Sample Acknowledgement Letter for Thesis
• 4 Conclusion

Tips on Writing Acknowledgement for Thesis

• Sincerity is Key: Ensure your acknowledgment reflects genuine gratitude.
• Be Specific: Mention names and their roles clearly.
• Professional Tone: Maintain a formal but heartfelt tone.
• Brevity Matters: Keep it concise, focusing on key contributors.

Best Acknowledgement for Thesis Samples

In this article, you’ll find ten meticulously crafted thesis acknowledgment examples, showcasing diverse styles and sentiments to help inspire your own. Whether it’s mentors, family, or colleagues, you’ll discover the perfect way to convey your gratitude.

Acknowledgement Sample for Thesis

I extend my sincere appreciation to everyone who played a role in guiding and supporting me throughout this thesis journey. I owe a special debt of gratitude to my thesis supervisor, Dr. [Supervisor’s Name], whose invaluable insights and guidance were instrumental in shaping this work. Their unwavering dedication to academic excellence was a constant source of motivation.

I must also express my heartfelt thanks to my family and friends who provided me with unwavering emotional support during the ups and downs of this project. Your unwavering belief in me, along with constructive feedback, was essential in navigating the challenges that arose throughout the process.

Acknowledgement for Thesis Submission

As I submit this thesis, it’s only fitting to express my heartfelt gratitude to those who contributed to its realization. My deepest thanks to my thesis advisor, [Advisor’s Name], whose expert guidance and unwavering support made this journey possible. Their dedication to nurturing academic excellence inspired me throughout.

I’m also indebted to my family and friends for the unwavering encouragement and emotional support they provided during this academic endeavor. Their steadfast belief in my abilities carried me through challenging times, and I am deeply appreciative of their contributions to my success.

Acknowledgement for Thesis Report

The completion of this thesis report is a significant milestone, and it wouldn’t have been attainable without the contributions of many. I am profoundly grateful to my thesis supervisor, Dr. [Supervisor’s Name], whose expertise and guidance were critical in the development of this work. Their unwavering commitment to scholarly excellence served as a constant source of inspiration.

I also wish to convey my appreciation to my family and friends for their enduring support and encouragement throughout this journey. Their belief in me provided the motivation to persevere during challenging periods, and I am truly thankful for their unwavering support.

Beautiful Thesis Acknowledgement

In this moment of achievement, it’s essential to express my gratitude to those who made this thesis journey beautiful. I extend my deepest appreciation to my thesis mentor, [Mentor’s Name], whose profound wisdom and continuous support have transformed my academic path. Their unwavering dedication to academic excellence was a shining example.

My heartfelt thanks go out to my family, friends, and loved ones, who have been a source of motivation and joy throughout this thesis project. Your unwavering belief in me, combined with your uplifting presence, painted this journey with beautiful colors and made it truly remarkable.

Acknowledging God in Thesis

As I complete this thesis, I wish to acknowledge the divine presence that guided me throughout this scholarly endeavor. My sincerest gratitude to the Almighty for granting me the strength, wisdom, and determination to bring this work to fruition. I acknowledge the blessings that have enabled me to pursue knowledge and produce this thesis.

Funny Thesis Acknowledgement

Completing this thesis was no easy feat, and I’d like to offer a lighthearted acknowledgment to those who contributed to the humor in this journey. My gratitude goes to my witty friends, who provided comic relief during stressful times, and my family, who managed to lighten the mood when needed. Laughter truly was the best medicine!

Acknowledgement in Thesis Writing

Acknowledging the completion of this thesis is a momentous task, and I want to express my appreciation for everyone who played a role. To begin, I’d like to thank my thesis advisor, [Advisor’s Name], whose expert guidance and patience were invaluable. Their wisdom and insights greatly contributed to the quality of this thesis.

I would also like to extend my gratitude to my colleagues and friends who offered support and encouragement. Their discussions and shared experiences enriched my work, and I’m grateful for their camaraderie.

Thesis Acknowledgement Sample

In writing this thesis, I’ve learned that acknowledgment is a fundamental part of scholarly work. With this sample, I aim to express my thanks to those who influenced and supported me. Firstly, I’m deeply indebted to my thesis supervisor, [Supervisor’s Name], whose unwavering commitment to research excellence has been a guiding light.

Additionally, I would like to acknowledge the contributions of my peers and the resources offered by the university. Their combined efforts have molded this thesis into what it is today.

Example of Acknowledgement in Thesis

For your reference, here’s an example of how acknowledgments can be included in a thesis. I am profoundly thankful to my thesis advisor, [Advisor’s Name], for their invaluable support and mentorship throughout this research journey. Their guidance was instrumental in shaping the research’s direction.

I also appreciate the guidance from my colleagues and the research resources that this institution provided. The synergy of all these factors, including my hard work and dedication, culminated in the completion of this thesis.

Sample Acknowledgement Letter for Thesis

Dear [Advisor’s Name],

I wish to extend my heartfelt gratitude for your unwavering support and guidance throughout the completion of my thesis. Your expertise, patience, and commitment to academic excellence have been a cornerstone of my research journey. Your thoughtful feedback and constant encouragement have not only honed my skills but also enriched the quality of this thesis.

I’d also like to acknowledge the contributions of my fellow researchers and the resources provided by our institution. Their collaborative efforts and the wealth of research materials and opportunities available have significantly influenced the outcome of this thesis.

This acknowledgement extends to my family and friends, whose belief in my abilities and encouragement have provided the emotional sustenance needed to complete this challenging task. Their unwavering support has been my motivation.

With gratitude,

[Your Name]

How to Write Acknowledgement for Thesis?

Writing an acknowledgement for your thesis involves expressing gratitude to the individuals and institutions that supported your research. Start by acknowledging your primary thesis advisor, followed by other mentors, colleagues, and family. Keep it concise and heartfelt, focusing on the contributions and support they provided. Remember to include any funding sources or institutions that aided your research.

What to Put in Acknowledgement Section of Thesis?

In the acknowledgement section of your thesis, you should express gratitude to the people and organizations who contributed to your research. This includes your thesis advisor, mentors, colleagues, and family. Be sure to mention any funding sources, grants, or institutions that supported your work. Keep the acknowledgements concise and focus on the assistance, guidance, and encouragement you received during your research.

What Are Some Thesis Acknowledgement Quotes?

“I can no other answer make but thanks, and thanks, and ever thanks.” – William Shakespeare

“Gratitude is the fairest blossom which springs from the soul.” – Henry Ward Beecher

“Acknowledging the good that you already have in your life is the foundation for all abundance.” – Eckhart Tolle

“Feeling gratitude and not expressing it is like wrapping a present and not giving it.” – William Arthur Ward

“In the end, we will remember not the words of our enemies, but the silence of our friends.” – Martin Luther King Jr.

“Acknowledgment is the first step of paying it forward.” – Robert Bach

An acknowledgement of thesis is more than just a formality; it embodies your gratitude and appreciation. As you explore the samples and gather inspiration from the tips provided, remember that thanking those who’ve played a part in your academic journey is not only courteous but also profoundly meaningful.

Acknowledgement to God for Project and Thesis (5 Samples)

Acknowledgement sample for undergraduate thesis (5 samples), leave a comment cancel reply.

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How to Draft the Acknowledgment Section of a Manuscript

What is the Purpose of the Acknowledgements Section in a Research Paper?

The acknowledgment section is an integral part of all academic research papers. It provides appropriate recognition to all contributors for their hard work. We discuss here,  the relevant guidelines for acknowledging contributors.

Defining Who Is Acknowledged

The acknowledgment section helps identify the contributors responsible for specific parts of the project. It can include:

• Non-authors (colleagues, friends, supervisor, etc.)
• Funding sources
• Editing services ,
• Administrative staff

In academic writing, the information presented in the acknowledgment section should be kept brief. It should only mention people directly involved with the project. In other words, one should not consider thanking ones’ parents for moral and financial support.

Acknowledging contributors is necessary. However, you must know the difference between an author and a contributor . The International Committee of Medical Journal Editors ( ICMJE ) defines four criteria to assign authorship.

He or she has to have

• Made substantial conceptual or design contributions or gathered and analyzed important data, and
• Either helped draft or critically revise the paper in keeping with important intellectual content, and
• Provided final approval before publishing, and
• Agreed to be accountable for the accuracy of the work

These authors and their affiliations will be listed at the beginning of the paper. The “corresponding author” will also be listed a second time and will directly correspond with the journal to ensure documentation requirements are met.

Many journals now ask that you provide the role of each author in your acknowledgment section. For example, a typical statement of authors’ contributions might be as follows (note that only last names are used unless ambiguous):

Smith conducted the data analysis and created the tables and figures. Jones provided his technological expertise for GIS tracking. Johnson provided a factual review and helped edit the manuscript.

This type of acknowledgment provides your reader with a good sense of who was responsible for each part of your research and manuscript.

Non-Author Contributors

There are many people involved in a research project who are not authors but have provided valuable contributions. For example, one person’s responsibility might be to seek project funding; another’s might be to supervise laboratory staff. A few others might have provided valuable services such as technical editing and writing or offering help in reviewing and revising the manuscript for grammar and syntax. These people should also be mentioned in the acknowledgment section of your manuscript.

Acknowledgment should also be provided  for  writing assistance, technical editing, language editing, and proofreading . Therefore, editing companies need to be duly acknowledged in professionally edited manuscripts as per the  ICMJE guidelines.

It is necessary to acknowledge editing companies in professionally edited manuscripts, even though these companies are paid for their work.

Acknowledgment Format

Unlike the main body of your paper, the format for your acknowledgment section can be more personal. It is permissible to use personal pronouns in this section. For example,

I thank the following individuals for their expertise and assistance throughout all aspects of our study and for their help in writing the manuscript.

Keep in mind that many guidelines indicate that funding sources be listed separately from the acknowledgment section. In addition, the sources (funding agencies) might have specific guidelines that you must follow. Please be sure to comply with these sources and your author guidelines.

For more information on authors and contributors , read articles on the Enago Academy website.

What types and formats of acknowledgments have you incorporated into your manuscripts? Please share your thoughts in the comments section below. Do you need help with manuscript editing ? Make sure you visit enago.com today!

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Acknowledgement in Research Paper | How to Write | Perfect Example

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What is acknowledgement in research paper?

Acknowledgement in a research paper is the section where the author expresses gratitude to individuals and organizations who have contributed to the completion of the study. This section is usually placed at the beginning or end of the paper and is an important part of the research process. It allows the author to recognize the support, assistance, and guidance they have received from others in the course of their research.

What is the purpose of acknowledgement in research paper?

The acknowledgement section is an opportunity for the author to show appreciation for anyone who has helped them in the research process, including mentors, advisors, colleagues, and funding agencies. It is also a way to acknowledge the contributions of participants, interviewees, or anyone else who has played a role in the study.

Acknowledgements can also include thanks to individuals who have provided critical feedback, technical assistance, or resources that have been essential to the research project. Overall, this section is a way for the author to show their appreciation for the collaborative and supportive nature of the research community.

How to write acknowledgement in research paper?

• Identify Key Contributors : Make a list of individuals and organizations that have contributed significantly to your research. This includes advisors, mentors, collaborators, funders, participants, and institutions.
• Understand the Purpose : Acknowledgments are meant to recognize and thank those who have supported or contributed to your research in various ways. Understand the purpose of this section is to express gratitude and recognize their contributions.
• Be Genuine and Specific : Your acknowledgments should be sincere and specific. Avoid generic expressions of thanks and instead, mention the specific contributions each person or organization made to your research.
• Start with Formality : Begin your acknowledgment section with a formal tone and expression of gratitude. Address individuals with their appropriate titles, such as Dr., Prof., Mr., or Ms., and mention any institutional affiliations if relevant.
• Personalize Your Thanks : Tailor your acknowledgments to acknowledge each individual’s specific contributions. Mention how their support, guidance, or expertise influenced your research or contributed to its success.
• Maintain Professionalism : While acknowledgments can be personal, maintain a professional tone and avoid overly informal language or colloquialisms. Remember that this section is part of your scholarly work.
• Consider Cultural Sensitivities : Be mindful of cultural norms and sensitivities when expressing gratitude, especially if your research involves international collaborations. Tailor your acknowledgments to reflect cultural expectations or customs, as appropriate.
• Proofread Carefully : Ensure your acknowledgments are free of grammatical errors and typos. Take the time to review and edit this section to ensure clarity and coherence.
• Respect Space Limitations : While it’s important to acknowledge all key contributors, be mindful of space limitations in your research paper. Prioritize mentioning those who made significant contributions while being respectful of length constraints.
• End on a Positive Note : Conclude your acknowledgment section with a positive and appreciative tone. Express your gratitude to everyone who supported your research journey, including family, friends, colleagues, and institutions.

Example of Acknowledgement in Research

I am immensely grateful to the individuals and organizations whose support and guidance have been instrumental in the completion of this research paper. Their assistance and expertise have significantly contributed to the development and refinement of my study.

Firstly, I extend my heartfelt appreciation to Dr. Aurora Rivera, my mentor and advisor throughout this research journey. Her insightful feedback, encouragement, and scholarly guidance have been invaluable in shaping the direction and methodology of my study.

I am also deeply thankful to Mr. Santiago Cruz, Director of Research at the Philippine Social Sciences Institute, for his generous support and assistance in accessing research resources. His expertise and encouragement have greatly facilitated the progress of my research.

Special gratitude is extended to my research collaborators, including Dr. Sofia Ramirez and Mr. Miguel Hernandez, for their collaborative efforts and insightful perspectives that have enriched the depth and analysis of my research findings.

I would like to acknowledge the valuable contributions of the staff and researchers at the Philippine Research Center for Social Sciences, whose support and expertise have been indispensable in navigating complex research methodologies and data analysis.

Furthermore, I extend my sincere appreciation to the participants of my study for their cooperation and willingness to share their experiences, which have provided essential insights and perspectives.

I wish to express my profound gratitude to my family and friends for their unwavering support, encouragement, and understanding throughout this research endeavor. Their belief in my abilities has been a constant source of motivation and inspiration.

Acknowledgement in Research Paper Example

We extend our heartfelt gratitude to the individuals and institutions whose unwavering support has been indispensable in the completion of this research paper. Their guidance, encouragement, and expertise have greatly contributed to the success of our study.

Firstly, we express our sincere appreciation to Dr. Juanita Cruz, Professor of Economics at the University of the Philippines, for her invaluable mentorship and insightful feedback throughout the research process. Her expertise in the field has been instrumental in shaping the direction of our study.

We are also indebted to Dr. Manuel Reyes, Director of the Philippine Economic Development Institute, for his generous assistance and provision of research resources. His support has been pivotal in enhancing the quality and depth of our analysis.

Special thanks are extended to our research collaborators, including Dr. Sofia Garcia from the Department of Political Science at Ateneo de Manila University, and Dr. Miguel Hernandez from the Department of Sociology at Mapua University. Their collaboration and expertise have enriched our research with diverse perspectives and profound insights.

We would like to acknowledge the invaluable assistance provided by the staff and researchers at the Philippine Institute for Development Studies, who generously shared their knowledge and resources throughout the duration of our study.

Furthermore, we extend our gratitude to the participants of our study, whose cooperation and willingness to share their experiences have been instrumental in shaping our findings.

• Acknowledgement for Thesis
• Acknowledgement for Dissertation

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Writing Acknowledgments for Your Research Paper

• Research Process
• Peer Review

In this article, we describe what types of contributions warrant mention in the acknowledgments section of a paper .

Updated on July 8, 2014

In another article , we discuss four criteria that must be met for an individual to qualify for manuscript authorship. In this article, we describe what types of contributions warrant mention in the acknowledgments section of a paper instead. The International Committee of Medical Journal Editors (ICMJE) describes several roles that merit acknowledgment, rather than authorship :

“acquisition of funding; general supervision of a research group or general administrative support; and writing assistance, technical editing, language editing, and proofreading.”

You should also acknowledge direct technical assistance, including help with animals, cells, equipment, patients, procedures, or techniques or provision of data, equipment, reagents, or samples, as well as more indirect assistance via intellectual discussions. Note that all of these contributions are typically more mechanical, indirect, and/or one-dimensional than those of authors. Additionally, some argue that individuals who provided help and could be chosen as a peer reviewer, leading to a potential conflict of interest, should be cited.

In any case, the ICMJE states that contributors may be cited individually or collectively and that their precise contributions should be specified.

e.g., “We thank Dr. X and Dr. Y for performing the surgeries” or “We thank the physicians who performed the surgeries"

Institutional affiliations may or may not be mentioned, depending on the journal's guidelines. Finally, the ICMJE encourages written permission from acknowledged individuals “because acknowledgment may imply endorsement.”

Funding sources should also be mentioned in the acknowledgments section, unless your target journal requires a separate section for this information. Whether the funding was partial or full, relevant grant numbers, and the author(s) who received the funding, if applicable, should be detailed as well. Note that acknowledging grants and fellowships is in fact required by many funding agencies and research institutions.

In contrast, contributions that are not specifically related to your research, including personal encouragement (e.g., by your friends or parents) and very general help (e.g., from a laboratory manager who purchases all supplies for your research group), should not be cited. Additionally, anonymous editors and peer reviewers are usually not thanked in the acknowledgments section; many journals (such as American Physical Society journals ) explicitly discourage this practice because it is difficult to comprehensively acknowledge all anonymous support and because this practice could potentially bias reviewers.

The writing style of acknowledgments sections may vary according to the journal, but generally, these sections are written in the first person and are as succinct as possible. A statement about conflicts of interest, citation of previous publication in poster or abstract form, and other information may also be included in this section, again depending on the journal. As you proceed through revisions for one journal or if you change your target journal, remember to reformat as necessary and to update your acknowledgments if additional help was obtained during the revision, such as with editing or new experiments.

Although an acknowledgments section may be appended to the end of your manuscript or relegated to a footnote, it is not a trivial component. By acknowledging all help received with your research, you are demonstrating your integrity as a researcher, which in turn encourages continued collaboration. You may also be bolstering your colleagues' careers, as being credited in an acknowledgments section is emerging as one of many gauges of a researcher's professional impact beyond citations (see ImpactStory , based on altmetrics ). Furthermore, information about who provided certain data, equipment, protocols, reagents, or samples may be of help to other researchers in your field.

This editing tip has hopefully elucidated what to include in the acknowledgments section of your manuscript and why this section is significant. If you have any comments or questions, please contact us . Best wishes in your research and writing!

Michaela Panter, PhD

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How to Write Acknowledgements

Last Updated: September 12, 2023 Fact Checked

This article was co-authored by Christopher Taylor, PhD . Christopher Taylor is an Adjunct Assistant Professor of English at Austin Community College in Texas. He received his PhD in English Literature and Medieval Studies from the University of Texas at Austin in 2014. There are 9 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 755,850 times.

Any time you publish work or are recognized publicly, it's good form to thank the people who've helped you along the way with an acknowledgment. It can be a tricky piece of writing, though. What tone to use? How formal should your thanks be? Who should you thank? Whether it be academic acknowledgments, public thanks, or other reasons for thanking people, wikiHow can help you offer your gratitude in style. See Step 1 for more information.

Academic Acknowledgment and Thank You Speech Templates

Writing Academic Acknowledgements

• The acknowledgment page can either be a list or a more fluid paragraph. It would be fine to write, "I would like to thank Professor Henderson, Dr. Matthews, etc." until you've worked your way through the list.
• It would also be perfectly acceptable to address each person individually and more personally: "I would like to thank Professor Henderson for her expert advice and encouragement throughout this difficult project, as well as Dr. Matthews for his brilliance in the lab." [2] X Research source
• Some people feel uncomfortable emphasizing certain people's help over other people's help, in which case the list form in alphabetical order is a perfectly acceptable method of writing an Acknowledgment.

• In general, it's helpful to think in groups, even going to far as to format all the thank-yous of a particular group in a single sentence: "I would like to thank Dr. Stevens, Dr. Smith, and Professors Clemons for their extraordinary support in this thesis process."
• If you worked with a small committee, it's customary and thoughtful to thank each person for the specific things they contributed to your work.

• If your scholarship at the University was supported by any fellowships or scholarships, it would also be appropriate to name them in this section: "This project would have been impossible without the support of the Katherine G. Katherine Foundation, the Reese's Peanut Butter scholarship, and the Guggenheim Group."

• Remember that your friendships and romances may change over the years, so it might be best to keep particularly mushy romances and declarations of love out of your acknowledgment page, so you won't have to see it later if it doesn't work out.
• It's generally best to avoid overtly personal anecdotes and inside jokes in an academic acknowledgements page. If you want to reference other students' constant joking around in the lab, say, it would be better to say, "Thanks to Joe and Katherine for their friendship in the lab" than "Thanks to Joe and Katherine for dunking my slides in Jell-O when I was hungover." [6] X Research source

Writing a Thank-You Speech

• Michael Jordan's Hall of Fame induction speech was widely criticized for being tone deaf and spiteful, talking down to many former opponents and somewhat tarnishing his great legacy. Don't fall in the same trap.

Writing Other Acknowledgements

• Like an academic publication, it's also important to remember to address any financial support you received during the publication of your book. If you received any artist residencies, grants, or fellowships while working on your book, you need to list them in the acknowledgments.
• Use your writing skills to approach the acknowledgment creatively. Authors like Lemony Snicket, Neil Gaiman, J.D. Salinger, and others have used the form for witty and usually-self deprecating anecdotes about the friends and cohorts they choose to thank.

• Friends and family
• Other bands who helped you along the way, lending gear or instruments
• Recording engineers and label folk
• Musical inspirations

• In the letter, explain your desire to thank them and explain the publication or event at which you'd like to thank them. Express your gratitude for their assistance and encourage them to get in touch to approve your acknowledgment. More often than not, they'll be flattered.

Expert Q&A

• Look at samples. Evaluating someone else's existing acknowledgements can help, especially if you are writing a specific kind of acknowledgement such as a thesis acknowledgement or other academic item. Thanks Helpful 46 Not Helpful 8

You Might Also Like

• ↑ https://esl.gatech.edu/sites/default/files/LI/li-how_to_write_acknowledgements_in_a_dissertation.pdf
• ↑ https://www.awelu.lu.se/referencing/writing-acknowledgements/
• ↑ https://us.sagepub.com/en-us/nam/funding-acknowledgements
• ↑ https://www.ref-n-write.com/blog/research-paper-example-writing-acknowledgements-appendix-sections-academic-phrasebank-vocabulary/
• ↑ https://gradschool.unc.edu/academics/thesis-diss/guide/ordercomponents.html#dedication
• ↑ http://www.katemessner.com/think-before-you-thank-writers-acknowledgments/
• ↑ https://owl.purdue.edu/owl/general_writing/the_writing_process/proofreading/index.html

About This Article

If you’ve published an academic work and you want to write acknowledgments, dedicate one page at the end of the document to thanking your supporters. You can write out your acknowledgments as a heartfelt paragraph thanking each person individually, or you can write a list in order of those who helped you the most, or even an alphabetical list if you’re uncomfortable emphasizing certain people over others. Include teachers, anyone who contributed to the project, personal supporters, and organizations or foundations which provided you with financial aid. For tips on writing acknowledgments for a literary work, keep reading! Did this summary help you? Yes No

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• Thesis & Dissertation Acknowledgements | Tips & Examples

Thesis & Dissertation Acknowledgements | Tips & Examples

Published on 4 May 2022 by Tegan George . Revised on 4 November 2022.

The acknowledgements section is your opportunity to thank those who have helped and supported you personally and professionally during your thesis or dissertation process.

Thesis or dissertation acknowledgements appear between your title page and abstract  and should be no longer than one page.

In your acknowledgements, it’s okay to use a more informal style than is usually permitted in academic writing , as well as first-person pronouns . Acknowledgements are not considered part of the academic work itself, but rather your chance to write something more personal.

To get started, download our step-by-step template in the format of your choice below. We’ve also included sample sentence starters to help you construct your acknowledgments section from scratch.

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Table of contents

Who to thank in your acknowledgements, how to write acknowledgements, acknowledgements section example, acknowledgements dos and don’ts, frequently asked questions.

Generally, there are two main categories of acknowledgements: professional and personal .

A good first step is to check your university’s guidelines, as they may have rules or preferences about the order, phrasing, or layout of acknowledgements. Some institutions prefer that you keep your acknowledgements strictly professional.

Regardless, it’s usually a good idea to place professional acknowledgements first, followed by any personal ones. You can then proceed by ranking who you’d like to thank from most formal to least.

• Chairs, supervisors, or defence committees
• Funding bodies
• Other academics (e.g., colleagues or cohort members)
• Editors or proofreaders
• Librarians, research/laboratory assistants, or study participants
• Family, friends, or pets

Typically, it’s only necessary to mention people who directly supported you during your thesis or dissertation. However, if you feel that someone like a secondary school physics teacher was a great inspiration on the path to your current research, feel free to include them as well.

Professional acknowledgements

It is crucial to avoid overlooking anyone who helped you professionally as you completed your thesis or dissertation. As a rule of thumb, anyone who directly contributed to your research should be mentioned.

A few things to keep in mind include:

• Even if you feel your chair didn’t help you very much, you should still thank them first to avoid looking like you’re snubbing them.
• Be sure to follow academic conventions, using full names with titles where appropriate.
• If several members of a group or organisation assisted you, mention the collective name only.
• Remember the ethical considerations around anonymised data. If you wish to protect someone’s privacy, use only their first name or a generic identifier (such as ‘the interviewees’).

Personal acknowledgements

There is no need to mention every member of your family or friend group. However, if someone was particularly inspiring or supportive, you may wish to mention them specifically. Many people choose to thank parents, partners, children, friends, and even pets, but you can mention anyone who offered moral support or encouragement, or helped you in a tangible or intangible way.

Some students may wish to dedicate their dissertation to a deceased influential person in their personal life. In this case, it’s okay to mention them first, before any professional acknowledgements.

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After you’ve compiled a list of who you’d like to thank, you can then sort your list into rank order. Separate everyone you listed into ‘major thanks’, ‘big thanks’, and ‘minor thanks’ categories.

• ‘Major thanks’ are given to people who your project would be impossible without. These are often predominantly professional acknowledgements, such as your advisor , chair, and committee, as well as any funders.
• ‘Big thanks’ are an in-between, for those who helped you along the way or helped you grow intellectually, such as classmates, peers, or librarians.
• ‘Minor thanks’ can be a catch-all for everyone else, especially those who offered moral support or encouragement. This can include personal acknowledgements, such as parents, partners, children, friends, or even pets.

How to phrase your acknowledgements

To avoid acknowledgements that sound repetitive or dull, consider changing up your phrasing. Here are some examples of common sentence starters you can use for each category.

Note that you do not need to write any sort of conclusion or summary at the end. You can simply end the acknowledgements with your last thank-you.

Here’s an example of how you can combine the different sentences to write your acknowledgements.

A simple construction consists of a sentence starter (in purple highlight ), followed by the person or entity mentioned (in green highlight ), followed by what you’re thanking them for (in yellow highlight .)

Acknowledgements

Words cannot express my gratitude to my professor and chair of my committee for her invaluable patience and feedback. I also could not have undertaken this journey without my defense committee, who generously provided knowledge and expertise. Additionally, this endeavor would not have been possible without the generous support from the MacArthur Foundation, who financed my research .

I am also grateful to my classmates and cohort members, especially my office mates, for their editing help, late-night feedback sessions, and moral support. Thanks should also go to the librarians, research assistants, and study participants from the university, who impacted and inspired me.

Lastly, I would be remiss in not mentioning my family, especially my parents, spouse, and children. Their belief in me has kept my spirits and motivation high during this process. I would also like to thank my cat for all the entertainment and emotional support.

• Write in first-person, professional language
• Thank your professional contacts first
• Include full names, titles, and roles of professional acknowledgements
• Include personal or intangible supporters, like friends, family, or even pets
• Mention funding bodies and what they funded
• Appropriately anonymise or group research participants or non-individual acknowledgments

Don’t:

• Use informal language or slang
• Go over one page in length
• Mention people who had only a peripheral or minor impact on your work

Prevent plagiarism, run a free check.

You may acknowledge God in your thesis or dissertation acknowledgements , but be sure to follow academic convention by also thanking the relevant members of academia, as well as family, colleagues, and friends who helped you.

Yes, it’s important to thank your supervisor(s) in the acknowledgements section of your thesis or dissertation .

Even if you feel your supervisor did not contribute greatly to the final product, you still should acknowledge them, if only for a very brief thank you. If you do not include your supervisor, it may be seen as a snub.

In the acknowledgements of your thesis or dissertation, you should first thank those who helped you academically or professionally, such as your supervisor, funders, and other academics.

Then you can include personal thanks to friends, family members, or anyone else who supported you during the process.

The acknowledgements are generally included at the very beginning of your thesis or dissertation, directly after the title page and before the abstract .

In a thesis or dissertation, the acknowledgements should usually be no longer than one page. There is no minimum length.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

George, T. (2022, November 04). Thesis & Dissertation Acknowledgements | Tips & Examples. Scribbr. Retrieved 24 June 2024, from https://www.scribbr.co.uk/thesis-dissertation/acknowledgements/

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Acknowledgement Letter

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How To Write Acknowledgement For Research Paper

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If you are thinking about How To Write Acknowledgment For Research Paper then you have come to the right place.

An acknowledgement section in a research paper is a place where you can express your gratitude to the people who have helped you with your research. This could include anyone who has provided support , guidance , or assistance during the research process.

For example, you might thank your advisors or professors for their guidance, your colleagues for their collaboration, librarians, lab assistants or a funding agency for their financial support and anyone else who has contributed to your research.

It is common to include an acknowledgement section in the beginning of a research paper, usually after the abstract and before the main body of the paper. The acknowledgement should be brief and to the point, and it is generally written in a formal, professional tone. You should avoid using casual language or personal anecdotes in this section.

The purpose of an acknowledgement is to express your gratitude to the people who have helped you with your research. It is a way to show that you appreciate the support and contributions of others, and it is an opportunity to thank them for their assistance. By including an acknowledgement in your research paper, you demonstrate that you are grateful for the help and support you have received, and you recognize the role that others have played in your research.

Here are some tips for writing an acknowledgement for a research paper:

• Start by thanking the people who have directly supported your research, such as your advisors and colleagues.
• Mention any funding agencies or organizations that provided financial support for your research.
• If you received assistance from librarians or other research staff, be sure to thank them as well.
• If you received help from any other individuals, such as lab assistants or research participants, be sure to include them in your acknowledgement.
• Keep your acknowledgement brief and to the point. You don’t need to go into great detail about the contributions of each person you are thanking.
• Use a formal, professional tone in your acknowledgement. This is not the place for casual language or personal anecdotes.

Here are a few acknowledgement samples for your research paper –

Table of Contents

Acknowledgement For Research Paper Sample

We are deeply grateful to all those who contributed to the success of this research project.

First and foremost, we would like to thank our primary supervisor, [Name], for their guidance, support, and encouragement throughout the entire process. Their mentorship and expertise were invaluable in helping us to shape the direction of our research and to bring our ideas to fruition.

We would also like to express our gratitude to the members of our research team, [Names], who provided valuable input, insights, and assistance at every stage of the project. Their contributions were critical to the success of this research, and we are deeply grateful for their hard work and dedication.

We would also like to thank the organizations and individuals who provided financial support for this research, including [Name] and [Name]. Without their generous contributions, this project would not have been possible.

Finally, we would like to extend our heartfelt thanks to all of the participants in our study, who generously shared their time, experiences, and insights with us. Their willingness to engage with our research was essential to the success of this project, and we are deeply grateful for their participation.

Overall, this research project would not have been possible without the support and contributions of so many people. We are deeply grateful to all of those who helped to make this project a reality, and we hope that our findings will make a meaningful contribution to the field.

Read Also: Get 15+ Acknowledgement Samples

Sample Acknowledgement For Research Paper

The completion of this research project would not have been possible without the contributions and support of many individuals and organizations. We are deeply grateful to all those who played a role in the success of this project.

We would like to thank [Name] for their invaluable input and support throughout the research process. Their insights and expertise were instrumental in shaping the direction of this project.

In addition, we would like to extend our sincere thanks to all of the participants in our study, who generously shared their time, experiences, and insights with us. Their willingness to engage with our research was essential to the success of this project, and we are deeply grateful for their participation.

Small Acknowledgement Sample For Research Paper

We would like to express our sincere gratitude to our advisors, Dr. Spirt Kular and Dr. Sonney Deom, for their invaluable guidance and support throughout the research process. We also wish to thank the XYZ Foundation for their financial support, as well as the librarians at the ABC Library for their assistance in finding the necessary research materials. Finally, we are grateful to all of the research participants who generously gave their time and effort to this project.

You can take the help online paraphrasing tool when crafting an acknowledgment for a research paper. They help you manipulate the formal tone of your text according to your needs and make sure your text stays sincere and relevant.

Using the paraphrase tool , you can express specific appreciation for individual contributions that fit the unique context of the paper. Ultimately, you write an acknowledgment that is as personalized and meaningful as possible.

Note: It’s important to note that the specific language and tone of your acknowledgement will depend on the context and the nature of the contributions made by the individuals or organizations you are thanking. It’s a good idea to be specific and sincere in your appreciation, and to tailor your acknowledgement to the specific contributions that were made.

Conclusion On How To Write Acknowledgement For Research Paper

In conclusion, writing an acknowledgement for a research paper is a crucial step in recognizing the contributions of others to your work. It is a way to show gratitude to those who have provided assistance, support, and guidance throughout the research process. When writing an acknowledgement, it is important to be sincere and specific in thanking those who have helped you. Be sure to mention individuals by name, and specify their roles and contributions.

Additionally, make sure to follow any specific guidelines or requirements for formatting and presenting the acknowledgement in your research paper. By following these tips, you can effectively convey your appreciation and recognition of the help you received while completing your research.

Read Also: Master Thesis Acknowledgement Sample

FAQs On How To Write Acknowledgement For Research Paper

1) What is a good sentence for acknowledgement? Ans: “I appreciate your efforts in completing this project on time.” “I want to acknowledge the hard work and dedication you have shown during this challenging year.” “I am grateful for your support and understanding during this difficult time.” It’s important to note that the specific wording and tone of an acknowledgement will depend on the context and the relationship between the speaker and the person being acknowledged.

2) Is conclusion and acknowledgement same? Ans: The conclusion is the final part of a written work that summarizes the main points and arguments. Acknowledgement is the act of recognizing or thanking someone or something for their contribution. These two things are often used in different contexts and for different purposes.

3) Who should I include in my acknowledgement for a research paper? Ans: It is appropriate to include anyone who has contributed significantly to your research, such as a supervisor, mentor, or colleague. You may also want to thank any individuals or organizations that provided financial or logistical support.

4) How should I structure my acknowledgement for a research paper? Ans: The structure of your acknowledgement will depend on the specific guidelines of the journal or publication you are submitting to. In general, it is common to include a brief paragraph at the beginning of the paper expressing your gratitude to those who have helped with the research. You can then list the names of the individuals or organizations you are thanking, along with a brief description of their contributions.

5) Is it necessary to include an acknowledgement in my research paper? Ans: It is not always required to include an acknowledgement in a research paper, but it is a common practice and can be a good way to show appreciation for the help and support you received during the research process.

6) Can I include personal thanks in my acknowledgement for a research paper? Ans: It is generally acceptable to include personal thanks in your acknowledgement, as long as it is done in a professional and respectful manner. You may want to thank family members or friends who provided emotional support during the research process, but be mindful of maintaining a professional tone and not going into too much detail about personal matters.

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How do you write an acknowledgement section without having anything to acknowledge?

If a journal requires an acknowledgement section, but you have nothing to acknowledge, how is this put best?

"The authors have nothing to acknowledge."? This sounds a bit arrogant to me.

The formatting instructions say : "Must be brief and must not include thanks to Editors or referees, effusive comments or dedications." It is given as optional; yet, the editor asked for it for the second time now.

• publications
• paper-submission
• acknowledgement

• 1 I removed a bunch of obsolete comments, some of which attempted at answering the question. Please make them proper answers because comments cannot be downvoted, edited or marked as accepted answers, bypassing the site's quality feedback. –  Massimo Ortolano Commented Jul 16, 2021 at 18:06

5 Answers 5

This research has received no external funding.

or something along those lines - or simply respond to the editor that you have not received any external funding, and thus do not see the need for an acknowledgement section.

One possibility is simply to extend your gratitutde to the reviewers and the editors.

According to this paper , the acknowledgement section can be quite hetereogeneous and can comprise the following sections. Perhaps you will find some inspiration here:

• Financial disclosure
• Conflict of interest
• Disclaimer (Ex.: " The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ")
• Peer communication (Ex.: " NN provided insightful discussions .")
• Investigation and Analysis
• Supervision and Management (Ex.: " Research included in this review was partly completed at the University XYZ under the supervision of NN. ")
• Materials and Resources
• Dissemination
• Organization (Ex.: " The second author would like to thank Organization XYZ. ")
• Combination
• Vague or other (Ex.: " We thank NN for their contribution during various stages of the paper preparation. ")

• 11 The formatting instructions say: "Must be brief and must not include thanks to Editors or referees, effusive comments or dedications." nature.com/documents/ncomms-formatting-instructions.pdf –  Libavi Commented Jul 14, 2021 at 11:17
• 21 @Libavius the instructions you link to for the Acknowledgements section clearly indicate that that section is “optional”. I think you are simply misinterpreting “must be brief” as “must be included, and be brief”, when what it actually means is “must be brief if included”. –  Dan Romik Commented Jul 14, 2021 at 15:30
• 61 "No undergrads were harmed in the writing of this paper." –  Paul Price Commented Jul 14, 2021 at 22:18
• 1 @PaulPrice isn't that an oxymoron? :) –  Prof. Falken Commented Jul 15, 2021 at 12:15
• @PaulPrice Pretty sure that the IRB wouldn't be too happy if they were. –  nick012000 Commented Jul 16, 2021 at 6:26

When you don’t have anything to acknowledge, there is no logical reason to include an acknowledgements section. I speculate that almost no reputable journal will insist on you adding such a section, or, if they do insist because they do have some logical reason why they want such sections included, they will provide instructions what to write in the case when the author has no one to acknowledge.

In the case in question ( the link you posted in the comments), the acknowledgements section is explicitly indicated as “optional”. Since you say the editor asked about it, tell them you will not be including an acknowledgements section. I hardly see how the editor can go against their own journal’s official instructions to authors of what papers should include.

tl;dr: Just ask the journal.

There is no reason to demonstrate your superior intelligence and conclusive skills in these situations; nor are we the best people to ask. Just write the journal's editor/secretariat/point-of-contact what they want, e.g. like so:

About the submission requirement of an acknowledgement section: Can you clarify which kinds of acknowledgements are expected? I'll mention I have not received any external funding for the research underlying my paper, so there is no funding body I could acknowledge.

and they'll tell you what needs to be in there - if anything.

• It is worthwhile to note that an author can succesfully submit a paper to one of the top journal of the Nature family, even if he/she/they are not able to conclude the social interaction with the editor without recurring to some sort of suggested behavior from the internet. Dictature of the masses, for the masses. Maybe there should be a IG:Academia, IG as per InstaGram ... –  EarlGrey Commented Jul 15, 2021 at 10:16

If you have nothing to acknowledge then you could use the space to do a land acknowledgement or note that black lives matter. The journal may not like it but they could hardly say it's not an acknowledgement.

• 7 Rest of the world does not give a damn about internal US politics. This really starts to be annoying (at best). Hurting political views of your readers is probably not a good idea. Unless this is a social sciences journal because everybody will agree (or pretend to). Or nobody will read it and be hurt : ) –  v1nce Commented Jul 15, 2021 at 22:07
• 1 Not understanding the downvotes here, the OP wants to know how to write an acknowledgement when nothing comes to mind. This answers provides US centric material to acknowledge. Downvoters may not agree or like this but there are other suggestions they also don't like and did not vote. –  kwame Commented Jul 16, 2021 at 13:00
• 1 @Kwarme Do you want to be (mis)judged on the sole merits of your work or on your political views ? Pro Choice or pro Life statements would also be acknowledgements. And both would be wrong imho. –  v1nce Commented Jul 16, 2021 at 16:21
• The downvotes likely are there because people consider the answer as well as such an acknowledgement as a troll move / political stunt. And most academics like the academic work to be free of political strife and wouldn't include their own political views for the same reason. It's simply a distraction and totally goes against the spirit of papers - putting the essential information into a condensed representation. –  Frank Hopkins Commented Jul 17, 2021 at 4:29

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• Published: 19 June 2024

Detecting hallucinations in large language models using semantic entropy

• Sebastian Farquhar   ORCID: orcid.org/0000-0002-9185-6415 1   na1 ,
• Jannik Kossen 1   na1 ,
• Lorenz Kuhn 1   na1 &
• Yarin Gal   ORCID: orcid.org/0000-0002-2733-2078 1  

Nature volume  630 ,  pages 625–630 ( 2024 ) Cite this article

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Large language model (LLM) systems, such as ChatGPT 1 or Gemini 2 , can show impressive reasoning and question-answering capabilities but often ‘hallucinate’ false outputs and unsubstantiated answers 3 , 4 . Answering unreliably or without the necessary information prevents adoption in diverse fields, with problems including fabrication of legal precedents 5 or untrue facts in news articles 6 and even posing a risk to human life in medical domains such as radiology 7 . Encouraging truthfulness through supervision or reinforcement has been only partially successful 8 . Researchers need a general method for detecting hallucinations in LLMs that works even with new and unseen questions to which humans might not know the answer. Here we develop new methods grounded in statistics, proposing entropy-based uncertainty estimators for LLMs to detect a subset of hallucinations—confabulations—which are arbitrary and incorrect generations. Our method addresses the fact that one idea can be expressed in many ways by computing uncertainty at the level of meaning rather than specific sequences of words. Our method works across datasets and tasks without a priori knowledge of the task, requires no task-specific data and robustly generalizes to new tasks not seen before. By detecting when a prompt is likely to produce a confabulation, our method helps users understand when they must take extra care with LLMs and opens up new possibilities for using LLMs that are otherwise prevented by their unreliability.

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‘Hallucinations’ are a critical problem 9 for natural language generation systems using large language models (LLMs), such as ChatGPT 1 or Gemini 2 , because users cannot trust that any given output is correct.

Hallucinations are often defined as LLMs generating “content that is nonsensical or unfaithful to the provided source content” 9 , 10 , 11 but they have come to include a vast array of failures of faithfulness and factuality. We focus on a subset of hallucinations which we call ‘confabulations’ 12 for which LLMs fluently make claims that are both wrong and arbitrary—by which we mean that the answer is sensitive to irrelevant details such as random seed. For example, when asked a medical question “What is the target of Sotorasib?” an LLM confabulates by sometimes answering KRASG12 ‘C’ (correct) and other times KRASG12 ‘D’ (incorrect) despite identical instructions. We distinguish this from cases in which a similar ‘symptom’ is caused by the following different mechanisms: when LLMs are consistently wrong as a result of being trained on erroneous data such as common misconceptions 13 ; when the LLM ‘lies’ in pursuit of a reward 14 ; or systematic failures of reasoning or generalization. We believe that combining these distinct mechanisms in the broad category hallucination is unhelpful. Our method makes progress on a portion of the problem of providing scalable oversight 15 by detecting confabulations that people might otherwise find plausible. However, it does not guarantee factuality because it does not help when LLM outputs are systematically bad. Nevertheless, we significantly improve question-answering accuracy for state-of-the-art LLMs, revealing that confabulations are a great source of error at present.

We show how to detect confabulations by developing a quantitative measure of when an input is likely to cause an LLM to generate arbitrary and ungrounded answers. Detecting confabulations allows systems built on LLMs to avoid answering questions likely to cause confabulations, to make users aware of the unreliability of answers to a question or to supplement the LLM with more grounded search or retrieval. This is essential for the critical emerging field of free-form generation in which naive approaches, suited to closed vocabulary and multiple choice, fail. Past work on uncertainty for LLMs has focused on simpler settings, such as classifiers 16 , 17 and regressors 18 , 19 , whereas the most exciting applications of LLMs relate to free-form generations.

The term hallucination in the context of machine learning originally comes from filling in ungrounded details, either as a deliberate strategy 20 or as a reliability problem 4 . The appropriateness of the metaphor has been questioned as promoting undue anthropomorphism 21 . Although we agree that metaphor must be used carefully with LLMs 22 , the widespread adoption of the term hallucination reflects the fact that it points to an important phenomenon. This work represents a step towards making that phenomenon more precise.

To detect confabulations, we use probabilistic tools to define and then measure the ‘semantic’ entropy of the generations of an LLM—an entropy that is computed over meanings of sentences. High entropy corresponds to high uncertainty 23 , 24 , 25 —so semantic entropy is one way to estimate semantic uncertainties. Semantic uncertainty, the broader category of measures we introduce, could be operationalized with other measures of uncertainty, such as mutual information, instead. Entropy in free-form generation is normally hard to measure because answers might mean the same thing (be semantically equivalent) despite being expressed differently (being syntactically or lexically distinct). This causes naive estimates of entropy or other lexical variation scores 26 to be misleadingly high when the same correct answer might be written in many ways without changing its meaning.

By contrast, our semantic entropy moves towards estimating the entropy of the distribution of meanings of free-form answers to questions, insofar as that is possible, rather than the distribution over the ‘tokens’ (words or word-pieces) which LLMs natively represent. This can be seen as a kind of semantic consistency check 27 for random seed variation. An overview of our approach is provided in Fig. 1 and a worked example in Supplementary Table 1 .

a , Naive entropy-based uncertainty measures variation in the exact answers, treating ‘Paris’, ‘It’s Paris’ and ‘France’s capital Paris’ as different. But this is unsuitable for language tasks for which sometimes different answers mean the same things. Our semantic entropy clusters answers which share meanings before computing the entropy. A low semantic entropy shows that the LLM is confident about the meaning. b , Semantic entropy can also detect confabulations in longer passages. We automatically decompose a long generated answer into factoids. For each factoid, an LLM generates questions to which that factoid might have been the answer. The original LLM then samples  M possible answers to these questions. Finally, we compute the semantic entropy over the answers to each specific question, including the original factoid. Confabulations are indicated by high average semantic entropy for questions associated with that factoid. Here, semantic entropy classifies Fact 1 as probably not a confabulation because generations often mean the same thing, despite very different wordings, which a naive entropy would have missed.

Intuitively, our method works by sampling several possible answers to each question and clustering them algorithmically into answers that have similar meanings, which we determine on the basis of whether answers in the same cluster entail each other bidirectionally 28 . That is, if sentence A entails that sentence B is true and vice versa, then we consider them to be in the same semantic cluster. We measure entailment using both general-purpose LLMs and natural language inference (NLI) tools developed specifically for detecting entailment for which we show direct evaluations in Supplementary Tables 2 and 3 and Supplementary Fig. 1 . Textual entailment has previously been shown to correlate with faithfulness 10 in the context of factual consistency 29 as well as being used to measure factuality in abstractive summarization 30 , especially when applied at the right granularity 31 .

Semantic entropy detects confabulations in free-form text generation across a range of language models and domains, without previous domain knowledge. Our evaluations cover question answering in trivia knowledge (TriviaQA 32 ), general knowledge (SQuAD 1.1; ref. 33 ), life sciences (BioASQ 34 ) and open-domain natural questions (NQ-Open 35 ) derived from actual queries to Google Search 36 . In addition, semantic entropy detects confabulations in mathematical word problems (SVAMP 37 ) and in a biography-generation dataset, FactualBio, accompanying this paper.

Our results for TriviaQA, SQuAD, BioASQ, NQ-Open and SVAMP are all evaluated context-free and involve sentence-length answers (96 ± 70 characters, mean ± s.d.) and use LLaMA 2 Chat (7B, 13B and 70B parameters) 38 , Falcon Instruct (7B and 40B) 39 and Mistral Instruct (7B) 40 . In the Supplementary Information , we further consider short-phrase-length answers. Results for FactualBio (442 ± 122 characters) use GPT-4 (ref. 1 ). At the time of writing, GPT-4 (ref. 1 ) did not expose output probabilities 41 or hidden states, although it does now. As a result, we propose a discrete approximation of our estimator for semantic entropy which allows us to run experiments without access to output probabilities, which we use for all GPT-4 results in this paper and which performs similarly well.

Our confabulation detection with semantic entropy is more robust to user inputs from previously unseen domains than methods which aim to ‘learn’ how to detect confabulations from a set of example demonstrations. Our method is unsupervised, meaning that we do not need labelled examples of confabulations. By contrast, supervised methods detect confabulations by learning patterns behind examples of confabulations, assuming that future questions preserve these patterns. But this assumption is often untrue in new situations or with confabulations that human overseers are unable to identify (compare Fig. 17 of ref. 24 ). As a strong supervised baseline, we compare to an embedding regression method inspired by ref. 24 which trains a logistic regression classifier to predict whether the model correctly answered a question on the basis of the final ‘embedding’ (hidden state) of the LLM. We also use the P (True) method 24 which looks at the probability with which an LLM predicts that the next token is ‘True’ when few-shot prompted to compare a main answer with ‘brainstormed’ alternatives.

Confabulations contribute substantially to incorrect answers given by language models. We show that semantic entropy can be used to predict many incorrect model answers and to improve question-answering accuracy by refusing to answer those questions the model is uncertain about. Corresponding to these two uses, we evaluate two main metrics. First, the widely used area under the receiver operating characteristic (AUROC) curve for the binary event that a given answer is incorrect. This measure captures both precision and recall and ranges from 0 to 1, with 1 representing a perfect classifier and 0.5 representing an un-informative classifier. We also show a new measure, the area under the ‘rejection accuracy’ curve (AURAC). This studies the case in which the confabulation detection score is used to refuse to answer the questions judged most likely to cause confabulations. Rejection accuracy is the accuracy of the answers of the model on the remaining questions and the area under this curve is a summary statistic over many thresholds (representative threshold accuracies are provided in Supplementary Material ). The AURAC captures the accuracy improvement which users would experience if semantic entropy was used to filter out questions causing the highest entropy.

Detecting confabulations in QA and math

In Fig. 2 , we show that both semantic entropy and its discrete approximation outperform our best baselines for sentence-length generations. These results are averaged across datasets and provide the actual scores on the held-out evaluation dataset. We report the raw average score across held-out evaluation datasets without standard error because the distributional characteristics are more a property of the models and datasets selected than the method. Consistency of relative results across different datasets is a stronger indicator of variation in this case.

Semantic entropy outperforms leading baselines and naive entropy. AUROC (scored on the y -axes) measures how well methods predict LLM mistakes, which correlate with confabulations. AURAC (likewise scored on the y -axes) measures the performance improvement of a system that refuses to answer questions which are judged likely to cause confabulations. Results are an average over five datasets, with individual metrics provided in the Supplementary Information .

Semantic entropy greatly outperforms the naive estimation of uncertainty using entropy: computing the entropy of the length-normalized joint probability of the token sequences. Naive entropy estimation ignores the fact that token probabilities also express the uncertainty of the model over phrasings that do not change the meaning of an output.

Our methods also outperform the supervised embedding regression method both in- and out-of-distribution. In pale-yellow bars we show that embedding regression performance deteriorates when its training data do not match the deployment distribution—which mirrors the common real-world case in which there is a distribution shift between training and deployment 42 —the plotted value is the average metric for embedding regression trained on one of the four ‘off-distribution’ datasets for that evaluation. This is critical because reliable uncertainty is most important when the data distribution shifts. Semantic entropy also outperforms P (True) which is supervised ‘in-context’; that is, it is adapted to the deployment task with a few training examples provided in the LLM prompt itself. The discrete variant of semantic entropy performs similarly to our standard estimator, despite not requiring exact output probabilities.

Averaged across the 30 combinations of tasks and models we study, semantic entropy achieves the best AUROC value of 0.790 whereas naive entropy (0.691), P (True) (0.698) and the embedding regression baseline (0.687) lag behind it. Semantic entropy performs well consistently, with stable performance (between 0.78 and 0.81 AUROC) across the different model families (LLaMA, Falcon and Mistral) and scales (from 7B to 70B parameters) which we study (we report summary statistics for each dataset and model as before). Although semantic entropy outperforms the baselines across all model sizes, P (True) seems to improve with model size, suggesting that it might become more competitive for very capable honest models in settings that the model understands well (which are, however, not the most important cases to have good uncertainty). We use ten generations to compute entropy, selected using analysis in Supplementary Fig. 2 . Further results for short-phrase generations are described in Supplementary Figs. 7 – 10 .

The results in Fig. 2 offer a lower bound on the effectiveness of semantic entropy at detecting confabulations. These evaluations determine whether semantic entropy and baseline methods can detect when the answers of the model are incorrect (which we validate against human correctness evaluations in Supplementary Table 4 ). In addition to errors from confabulations (arbitrary incorrectness), this also includes other types of mistakes for which semantic entropy is not suited, such as consistent errors learned from the training data. The fact that methods such as embedding regression are able to spot other kinds of errors, not just confabulations, but still are outperformed by semantic entropy, suggests that confabulations are a principal category of errors for actual generations.

Examples of questions and answers from TriviaQA, SQuAD and BioASQ, for LLaMA 2 Chat 70B, are shown in Table 1 . These illustrate how only semantic entropy detects when the meaning is constant but the form varies (the first row of the table) whereas semantic entropy and naive entropy both correctly predict the presence of confabulations when the form and meaning vary together (second row) and predict the absence of confabulations when the form and meaning are both constant across several resampled generations (third row). In the final row, we give an example in which semantic entropy is erroneously high as a result of overly sensitive semantic clustering relative to the reference answer. Our clustering method distinguishes the answers which provide a precise date from those which only provide a year. For some contexts that would have been correct but in this context the distinction between the specific day and the year is probably irrelevant. This highlights the importance of context and judgement in clustering, especially in subtle cases, as well as the shortcomings of evaluating against fixed reference answers which do not capture the open-ended flexibility of conversational deployments of LLMs.

Detecting confabulations in biographies

Semantic entropy is most natural for sentences that express a single proposition but the idea of semantic equivalence is trickier to apply to longer passages which express many propositions which might only agree partially 43 . Nevertheless, we can use semantic entropy to detect confabulations in longer generations, such as entire paragraphs of text. To show this, we develop a dataset of biographical generations from GPT-4 (v.0613) for 21 individuals notable enough to have their own Wikipedia page but without extensive online biographies. From each biography generated by GPT-4, we automatically extract propositional factual claims about the individual (150 factual claims in total), which we manually label as true or false.

Applying semantic entropy to this problem is challenging. Naively, one might simply regenerate each sentence (conditioned on the text so far) and then compute semantic entropy over these regenerations. However, the resampled sentences often target different aspects of the biography: for example, one time describing family and the next time profession. This is analogous to the original problem semantic entropy was designed to resolve: the model is uncertain about the right ordering of facts, not about the facts themselves. To address this, we break down the entire paragraph into factual claims and reconstruct questions which might have been answered by those claims. Only then do we apply semantic entropy (Fig. 1 ) by generating three new answers to each question (selected with analysis in Supplementary Figs. 3 and 4 ) and computing the semantic entropy over those generations plus the original factual claim. We aggregate these by averaging the semantic entropy over all the questions to get an uncertainty score for each proposition, which we use to detect confabulations. Unaggregated results are shown in Supplementary Figs. 5 and 6 .

As GPT-4 did not allow access to the probability of the generation at the time of writing, we use a discrete variant of semantic entropy which makes the further approximation that we can infer a discrete empirical distribution over semantic meaning clusters from only the generations ( Methods ). This allows us to compute semantic entropy using only the black-box outputs of an LLM. However, we were unable to compute the naive entropy baseline, the standard semantic entropy estimator or the embedding regression baseline for GPT-4 without output probabilities and embeddings.

In Fig. 3 we show that the discrete variant of semantic entropy effectively detects confabulations on this dataset. Its AUROC and AURAC are higher than either a simple ‘self-check’ baseline—which just asks the LLM whether the factoid is likely to be true—or a variant of P (True) which has been adapted to work for the paragraph-length setting. Discrete semantic entropy has better rejection accuracy performance until 20% of the questions have been rejected at which point P (True) has a narrow edge. This indicates that the questions predicted to cause confabulations are indeed more likely to be wrong.

The discrete variant of our semantic entropy estimator outperforms baselines both when measured by AUROC and AURAC metrics (scored on the y -axis). The AUROC and AURAC are substantially higher than for both baselines. At above 80% of questions being answered, semantic entropy has the highest accuracy. Only when the top 20% of answers judged most likely to be confabulations are rejected does the answer accuracy on the remainder for the P (True) baseline exceed semantic entropy.

Our probabilistic approach, accounting for semantic equivalence, detects an important class of hallucinations: those that are caused by a lack of LLM knowledge. These are a substantial portion of the failures at present and will continue even as models grow in capabilities because situations and cases that humans cannot reliably supervise will persist. Confabulations are a particularly noteworthy failure mode for question answering but appear in other domains too. Semantic entropy needs no previous domain knowledge and we expect that algorithmic adaptations to other problems will allow similar advances in, for example, abstractive summarization. In addition, extensions to alternative input variations such as rephrasing or counterfactual scenarios would allow a similar method to act as a form of cross-examination 44 for scalable oversight through debate 45 .

The success of semantic entropy at detecting errors suggests that LLMs are even better at “knowing what they don’t know” than was argued by ref. 24 —they just don’t know they know what they don’t know. Our method explicitly does not directly address situations in which LLMs are confidently wrong because they have been trained with objectives that systematically produce dangerous behaviour, cause systematic reasoning errors or are systematically misleading the user. We believe that these represent different underlying mechanisms—despite similar ‘symptoms’—and need to be handled separately.

One exciting aspect of our approach is the way it makes use of classical probabilistic machine learning methods and adapts them to the unique properties of modern LLMs and free-form language generation. We hope to inspire a fruitful exchange of well-studied methods and emerging new problems by highlighting the importance of meaning when addressing language-based machine learning problems.

Semantic entropy as a strategy for overcoming confabulation builds on probabilistic tools for uncertainty estimation. It can be applied directly to any LLM or similar foundation model without requiring any modifications to the architecture. Our ‘discrete’ variant of semantic uncertainty can be applied even when the predicted probabilities for the generations are not available, for example, because access to the internals of the model is limited.

In this section we introduce background on probabilistic methods and uncertainty in machine learning, discuss how it applies to language models and then discuss our contribution, semantic entropy, in detail.

Uncertainty and machine learning

We aim to detect confabulations in LLMs, using the principle that the model will be uncertain about generations for which its output is going to be arbitrary.

One measure of uncertainty is the predictive entropy of the output distribution, which measures the information one has about the output given the input 25 . The predictive entropy (PE) for an input sentence x is the conditional entropy ( H ) of the output random variable Y with realization y given x ,

A low predictive entropy indicates an output distribution which is heavily concentrated whereas a high predictive entropy indicates that many possible outputs are similarly likely.

Aleatoric and epistemic uncertainty

We do not distinguish between aleatoric and epistemic uncertainty in our analysis. Researchers sometimes separate aleatoric uncertainty (uncertainty in the underlying data distribution) from epistemic uncertainty (caused by having only limited information) 46 . Further advances in uncertainty estimation which separate these kinds of uncertainty would enhance the potential for our semantic uncertainty approach by allowing extensions beyond entropy.

Joint probabilities of sequences of tokens

Generative LLMs produce strings of text by selecting tokens in sequence. Each token is a wordpiece that often represents three or four characters (though especially common sequences and important words such as numbers typically get their own token). To compute entropies, we need access to the probabilities the LLM assigns to the generated sequence of tokens. The probability of the entire sequence, s , conditioned on the context, x , is the product of the conditional probabilities of new tokens given past tokens, whose resulting log-probability is \(\log P({\bf{s}}| {\boldsymbol{x}})={\sum }_{i}\log P({s}_{i}| {{\bf{s}}}_{ < i},{\boldsymbol{x}})\) , where s i is the i th output token and s < i denotes the set of previous tokens.

Length normalization

When comparing the log-probabilities of generated sequences, we use ‘length normalization’, that is, we use an arithmetic mean log-probability, \(\frac{1}{N}{\sum }_{i}^{N}\log P({s}_{i}| {{\bf{s}}}_{ < i},{\boldsymbol{x}})\) , instead of the sum. In expectation, longer sequences have lower joint likelihoods because of the conditional independence of the token probabilities 47 . The joint likelihood of a sequence of length N shrinks exponentially in N . Its negative log-probability therefore grows linearly in N , so longer sentences tend to contribute more to entropy. We therefore interpret length-normalizing the log-probabilities when estimating the entropy as asserting that the expected uncertainty of generations is independent of sentence length. Length normalization has some empirical success 48 , including in our own preliminary experiments, but little theoretical justification in the literature.

Principles of semantic uncertainty

If we naively calculate the predictive entropy directly from the probabilities of the generated sequence of tokens, we conflate the uncertainty of the model over the meaning of its answer with the uncertainty over the exact tokens used to express that meaning. For example, even if the model is confident in the meaning of a generation, there are still usually many different ways for phrasing that generation without changing its meaning. For the purposes of detecting confabulations, the uncertainty of the LLM over meanings is more important than the uncertainty over the exact tokens used to express those meanings.

Our semantic uncertainty method therefore seeks to estimate only the uncertainty the LLM has over the meaning of its generation, not the choice of words. To do this, we introduce an algorithm that clusters model generations by meaning and subsequently calculates semantic uncertainty. At a high level this involves three steps:

Generation: sample output sequences of tokens from the predictive distribution of a LLM given a context x .

Clustering: cluster sequences by their meaning using our clustering algorithm based on bidirectional entailment.

Entropy estimation: estimate semantic entropy by summing probabilities of sequences that share a meaning following equation ( 2 ) and compute their entropy.

Generating a set of answers from the model

Given some context x as input to the LLM, we sample M sequences, { s (1) , …,  s ( M ) } and record their token probabilities, { P ( s (1) ∣ x ), …,  P ( s ( M ) ∣ x )}. We sample all our generations from a single model, varying only the random seed used for sampling from the token probabilities. We do not observe the method to be particularly sensitive to details of the sampling scheme. In our implementation, we sample at temperature 1 using nucleus sampling ( P  = 0.9) (ref. 49 ) and top- K sampling ( K  = 50) (ref. 50 ). We also sample a single generation at low temperature (0.1) as an estimate of the ‘best generation’ of the model to the context, which we use to assess the accuracy of the model. (A lower sampling temperature increases the probability of sampling the most likely tokens).

Clustering by semantic equivalence

To estimate semantic entropy we need to cluster generated outputs from the model into groups of outputs that mean the same thing as each other.

This can be described using ‘semantic equivalence’ which is the relation that holds between two sentences when they mean the same thing. We can formalize semantic equivalence mathematically. Let the space of tokens in a language be \({\mathcal{T}}\) . The space of all possible sequences of tokens of length N is then \({{\mathcal{S}}}_{N}\equiv {{\mathcal{T}}}^{N}\) . Note that N can be made arbitrarily large to accommodate whatever size of sentence one can imagine and one of the tokens can be a ‘padding’ token which occurs with certainty for each token after the end-of-sequence token. For some sentence \({\bf{s}}\in {{\mathcal{S}}}_{N}\) , composed of a sequence of tokens, \({s}_{i}\in {\mathcal{T}}\) , there is an associated meaning. Theories of meaning are contested 51 . However, for specific models and deployment contexts many considerations can be set aside. Care should be taken comparing very different models and contexts.

Let us introduce a semantic equivalence relation, E (  ⋅  ,  ⋅  ), which holds for any two sentences that mean the same thing—we will operationalize this presently. Recall that an equivalence relation is any reflexive, symmetric and transitive relation and that any equivalence relation on a set corresponds to a set of equivalence classes. Each semantic equivalence class captures outputs that can be considered to express the same meaning. That is, for the space of semantic equivalence classes \({\mathcal{C}}\) the sentences in the set \(c\in {\mathcal{C}}\) can be regarded in many settings as expressing a similar meaning such that \(\forall {\bf{s}},{{\bf{s}}}^{{\prime} }\in c:E({\bf{s}},{{\bf{s}}}^{{\prime} })\) . So we can build up these classes of semantically equivalent sentences by checking if new sentences share a meaning with any sentences we have already clustered and, if so, adding them into that class.

We operationalize E (  ⋅  ,  ⋅  ) using the idea of bidirectional entailment, which has a long history in linguistics 52 and natural language processing 28 , 53 , 54 . A sequence, s , means the same thing as a second sequence, s ′, only if the sequences entail (that is, logically imply) each other. For example, ‘The capital of France is Paris’ entails ‘Paris is the capital of France’ and vice versa because they mean the same thing. (See later for a discussion of soft equivalence and cases in which bidirectional entailment does not guarantee equivalent meanings).

Importantly, we require that the sequences mean the same thing with respect to the context—key meaning is sometimes contained in the context. For example, ‘Paris’ does not entail ‘The capital of France is Paris’ because ‘Paris’ is not a declarative sentence without context. But in the context of the question ‘What is the capital of France?’, the one-word answer does entail the longer answer.

Detecting entailment has been the object of study of a great deal of research in NLI 55 . We rely on language models to predict entailment, such as DeBERTa-Large-MNLI 56 , which has been trained to predict entailment, or general-purpose LLMs such as GPT-3.5 (ref. 57 ), which can predict entailment given suitable prompts.

We then cluster sentences according to whether they bidirectionally entail each other using the algorithm presented in Extended Data Fig. 1 . Note that, to check if a sequence should be added to an existing cluster, it is sufficient to check if the sequence bidirectionally entails any of the existing sequences in that cluster (we arbitrarily pick the first one), given the transitivity of semantic equivalence. If a sequence does not share meaning with any existing cluster, we assign it its own cluster.

Computing the semantic entropy

Having determined the classes of generated sequences that mean the same thing, we can estimate the likelihood that a sequence generated by the LLM belongs to a given class by computing the sum of the probabilities of all the possible sequences of tokens which can be considered to express the same meaning as

Formally, this treats the output as a random variable whose event-space is the space of all possible meaning-classes, C , a sub- σ -algebra of the standard event-space S . We can then estimate the semantic entropy (SE) as the entropy over the meaning-distribution,

There is a complication which prevents direct computation: we do not have access to every possible meaning-class c . Instead, we can only sample c from the sequence-generating distribution induced by the model. To handle this, we estimate the expectation in equation ( 3 ) using a Rao–Blackwellized Monte Carlo integration over the semantic equivalence classes C ,

where \(P({C}_{i}| {\boldsymbol{x}})=\frac{P({c}_{i}| {\boldsymbol{x}})}{{\sum }_{c}P(c| {\boldsymbol{x}})}\) estimates a categorical distribution over the cluster meanings, that is, ∑ i P ( C i ∣ x ) = 1. Without this normalization step cluster ‘probabilities’ could exceed one because of length normalization, resulting in degeneracies. Equation ( 5 ) is the estimator giving our main method that we refer to as semantic entropy throughout the text.

For scenarios in which the sequence probabilities are not available, we propose a variant of semantic entropy which we call ‘discrete’ semantic entropy. Discrete semantic entropy approximates P ( C i ∣ x ) directly from the number of generations in each cluster, disregarding the token probabilities. That is, we approximate P ( C i ∣ x ) as \({\sum }_{1}^{M}\frac{{I}_{c={C}_{i}}}{M}\) , the proportion of all the sampled answers which belong to that cluster. Effectively, this just assumes that each output that was actually generated was equally probable—estimating the underlying distribution as the categorical empirical distribution. In the limit of M the estimator converges to equation ( 5 ) by the law of large numbers. We find that discrete semantic entropy results in similar performance empirically.

We provide a worked example of the computation of semantic entropy in Supplementary Note  1 .

Semantic entropy is designed to detect confabulations, that is, model outputs with arbitrary meaning. In our experiments, we use semantic uncertainty to predict model accuracy, demonstrating that confabulations make up a notable fraction of model mistakes. We further show that semantic uncertainty can be used to improve model accuracy by refusing to answer questions when semantic uncertainty is high. Last, semantic uncertainty can be used to give users a way to know when model generations are probably unreliable.

We use the datasets BioASQ 34 , SQuAD 33 , TriviaQA 32 , SVAMP 37 and NQ-Open 35 . BioASQ is a life-sciences question-answering dataset based on the annual challenge of the same name. The specific dataset we use is based on the QA dataset from Task B of the 2023 BioASQ challenge (11B). SQuAD is a reading comprehension dataset whose context passages are drawn from Wikipedia and for which the answers to questions can be found in these passages. We use SQuAD 1.1 which excludes the unanswerable questions added in v.2.0 that are deliberately constructed to induce mistakes so they do not in practice cause confabulations to occur. TriviaQA is a trivia question-answering dataset. SVAMP is a word-problem maths dataset containing elementary-school mathematical reasoning tasks. NQ-Open is a dataset of realistic questions aggregated from Google Search which have been chosen to be answerable without reference to a source text. For each dataset, we use 400 train examples and 400 test examples randomly sampled from the original larger dataset. Note that only some of the methods require training, for example semantic entropy does not use the training data. If the datasets themselves are already split into train and test (or validation) samples, we sample our examples from within the corresponding split.

All these datasets are free-form, rather than multiple choice, because this better captures the opportunities created by LLMs to produce free-form sentences as answers. We refer to this default scenario as our ‘sentence-length’ experiments. In Supplementary Note  7 , we also present results for confabulation detection in a ‘short-phrase’ scenario, in which we constrain model answers on these datasets to be as concise as possible.

To make the problems more difficult and induce confabulations, we do not provide the context passages for any of the datasets. When the context passages are provided, the accuracy rate is too high for these datasets for the latest generations of models to meaningfully study confabulations.

For sentence-length generations we use: Falcon 39 Instruct (7B and 40B), LLaMA 2 Chat 38 (7B, 13B and 70B) and Mistral 40 Instruct (7B).

In addition to reporting results for semantic entropy, discrete semantic entropy and naive entropy, we consider two strong baselines.

Embedding regression is a supervised baseline inspired by the P (IK) method 24 . In that paper, the authors fine-tune their proprietary LLM on a dataset of questions to predict whether the model would have been correct. This requires access to a dataset of ground-truth answers to the questions. Rather than fine-tuning the entire LLM in this way, we simply take the final hidden units and train a logistic regression classifier to make the same prediction. By contrast to their method, this is much simpler because it does not require fine-tuning the entire language model, as well as being more reproducible because the solution to the logistic regression optimization problem is not as seed-dependent as the fine-tuning procedure. As expected, this supervised approach performs well in-distribution but fails when the distribution of questions is different from that on which the classifier is trained.

The second baseline we consider is the P (True) method 24 , in which the model first samples M answers (identically to our semantic entropy approach) and then is prompted with the list of all answers generated followed by the highest probability answer and a question whether this answer is “(a) True” or “(b) False”. The confidence score is then taken to be the probability with which the LLM responds with ‘a’ to the multiple-choice question. The performance of this method is boosted with a few-shot prompt, in which up to 20 examples from the training set are randomly chosen, filled in as above, but then provided with the actual ground truth of whether the proposed answer was true or false. In this way, the method can be considered as supervised ‘in-context’ because it makes use of some ground-truth training labels but can be used without retraining the model. Because of context-size constraints, this method cannot fit a full 20 few-shot examples in the context when input questions are long or large numbers of generations are used. As a result, we sometimes have to reduce the number of few-shot examples to suit the context size and we note this in the  Supplementary Material .

Entailment estimator

Any NLI classification system could be used for our bidirectional entailment clustering algorithm. We consider two different kinds of entailment detector.

One option is to use an instruction-tuned LLM such as LLaMA 2, GPT-3.5 (Turbo 1106) or GPT-4 to predict entailment between generations. We use the following prompt:

We are evaluating answers to the question {question} Here are two possible answers: Possible Answer 1: {text1} Possible Answer 2: {text2} Does Possible Answer 1 semantically entail Possible Answer 2? Respond with entailment, contradiction, or neutral.

Alternatively, we consider using a language model trained for entailment prediction, specifically the DeBERTa-large model 56 fine-tuned on the NLI dataset MNLI 58 . This builds on past work towards paraphrase identification based on embedding similarity 59 , 60 and BERT-style models 61 , 62 . We template more simply, checking if DeBERTa predicts entailment between the concatenation of the question and one answer and the concatenation of the question and another answer. Note that DeBERTa-large is a relatively lightweight model with only 1.5B parameters which is much less powerful than most of the LLMs under study.

In Supplementary Note 2 , we carefully evaluate the benefits and drawbacks of these methods for entailment prediction. We settle on using GPT-3.5 with the above prompt, as its entailment predictions agree well with human raters and lead to good confabulation detection performance.

In Supplementary Note  3 , we provide a discussion of the computational cost and choosing the number of generations for reliable clustering.

Prompting templates

We use a simple generation template for all sentence-length answer datasets:

Answer the following question in a single brief but complete sentence. Question: {question} Answer:

Metrics and accuracy measurements

We use three main metrics to evaluate our method: AUROC, rejection accuracy and AURAC. Each of these is grounded in an automated factuality estimation measurement relative to the reference answers provided by the datasets that we use.

AUROC, rejection accuracy and AURAC

First, we use the AUROC curve, which measures the reliability of a classifier accounting for both precision and recall. The AUROC can be interpreted as the probability that a randomly chosen correct answer has been assigned a higher confidence score than a randomly chosen incorrect answer. For a perfect classifier, this is 1.

Second, we compute the ‘rejection accuracy at X %’, which is the question-answering accuracy of the model on the most-confident X % of the inputs as identified by the respective uncertainty method. If an uncertainty method works well, predictions on the confident subset should be more accurate than predictions on the excluded subset and the rejection accuracy should increase as we reject more inputs.

To summarize this statistic we compute the AURAC—the total area enclosed by the accuracies at all cut-off percentages X %. This should increase towards 1 as given uncertainty method becomes more accurate and better at detecting likely-inaccurate responses but it is more sensitive to the overall accuracy of the model than the AUROC metric.

In Supplementary Note  5 , we provide the unaggregated rejection accuracies for sentence-length generations.

Assessing accuracy

For the short-phrase-length generation setting presented in Supplementary Note  7 , we simply assess the accuracy of the generations by checking if the F1 score of the commonly used SQuAD metric exceeds 0.5. There are limitations to such simple scoring rules 63 but this method is widely used in practice and its error is comparatively small on these standard datasets.

For our default scenario, the longer sentence-length generations, this measure fails, as the overlap between the short reference answer and our long model answer is invariably too small. For sentence-length generations, we therefore automatically determine whether an answer to the question is correct or incorrect by using GPT-4 to compare the given answer to the reference answer. We use the template:

We are assessing the quality of answers to the following question: {question} The expected answer is: {reference answer} The proposed answer is: {predicted answer} Within the context of the question, does the proposed answer mean the same as the expected answer? Respond only with yes or no.

We make a small modification for datasets with several reference answers: line two becomes “The following are expected answers to this question:” and the final line asks “does the proposed answer mean the same as any of the expected answers?”.

In Supplementary Note 6 , we check the quality of our automated ground-truth evaluations against human judgement by hand. We find that GPT-4 gives the best results for determining model accuracy and thus use it in all our sentence-length experiments.

In this section we describe the application of semantic entropy to confabulation detection in longer model generations, specifically paragraph-length biographies.

We introduce a biography-generation dataset—FactualBio—available alongside this paper. FactualBio is a collection of biographies of individuals who are notable enough to have Wikipedia pages but not notable enough to have large amounts of detailed coverage, generated by GPT-4 (v.0613). To generate the dataset, we randomly sampled 21 individuals from the WikiBio dataset 64 . For each biography, we generated a list of factual claims contained in each biography using GPT-4, with 150 total factual claims (the total number is only coincidentally a round number). For each of these factual claims, we manually determined whether the claim was correct or incorrect. Out of 150 claims, 45 were incorrect. As before, we apply confabulation detection to detect incorrect model predictions, even though there may be model errors which are not confabulations.

Prompting and generation

Given a paragraph-length piece of LLM-generated text, we apply the following sequence of steps:

Automatically decompose the paragraph into specific factual claims using an LLM (not necessarily the same as the original).

For each factual claim, use an LLM to automatically construct Q questions which might have produced that claim.

For each question, prompt the original LLM to generate M answers.

For each question, compute the semantic entropy of the answers, including the original factual claim.

Average the semantic entropies over the questions to arrive at a score for the original factual claim.

We pursue this slightly indirect way of generating answers because we find that simply resampling each sentence creates variation unrelated to the uncertainty of the model about the factual claim, such as differences in paragraph structure.

We decompose the paragraph into factual claims using the following prompt:

Please list the specific factual propositions included in the answer above. Be complete and do not leave any factual claims out. Provide each claim as a separate sentence in a separate bullet point.

We found that we agreed with the decompositions in all cases in the dataset.

We then generate six questions for each of the facts from the decomposition. We generate these questions by prompting the model twice with the following:

Following this text: {text so far} You see the sentence: {proposition} Generate a list of three questions, that might have generated the sentence in the context of the preceding original text, as well as their answers. Please do not use specific facts that appear in the follow-up sentence when formulating the question. Make the questions and answers diverse. Avoid yes-no questions. The answers should not be a full sentence and as short as possible, e.g. only a name, place, or thing. Use the format “1. {question} – {answer}”.

These questions are not necessarily well-targeted and the difficulty of this step is the main source of errors in the procedure. We generate three questions with each prompt, as this encourages diversity of the questions, each question targeting a different aspect of the fact. However, we observed that the generated questions will sometimes miss obvious aspects of the fact. Executing the above prompt twice (for a total of six questions) can improve coverage. We also ask for brief answers because the current version of GPT-4 tends to give long, convoluted and highly hedged answers unless explicitly told not to.

Then, for each question, we generate three new answers using the following prompt:

We are writing an answer to the question “{user question}”. So far we have written: {text so far} The next sentence should be the answer to the following question: {question} Please answer this question. Do not answer in a full sentence. Answer with as few words as possible, e.g. only a name, place, or thing.

We then compute the semantic entropy over these answers plus the original factual claim. Including the original fact ensures that the estimator remains grounded in the original claim and helps detect situations in which the question has been interpreted completely differently from the original context. We make a small modification to handle the fact that GPT-4 generations often include refusals to answer questions. These refusals were not something we commonly observe in our experiments with LLaMA 2, Falcon or Mistral models. If more than half of the answers include one of the strings ‘not available’, ‘not provided’, ‘unknown’ or ‘unclear’ then we treat the semantic uncertainty as maximal.

We then average the semantic entropies for each question corresponding to the factual claim to get an entropy for this factual claim.

Despite the extra assumptions and complexity, we find that this method greatly outperforms the baselines.

To compute semantic entailment between the original claim and regenerated answers, we rely on the DeBERTa entailment prediction model as we find empirically that DeBERTa predictions result in higher train-set AUROC than other methods. Because DeBERTa has slightly lower recall than GPT-3.5/4, we use a modified set-up for which we say the answers mean the same as each other if at least one of them entails the other and neither is seen to contradict the other—a kind of ‘non-defeating’ bidirectional entailment check rather than true bidirectional entailment. The good performance of DeBERTa in this scenario is not surprising as both factual claims and regenerated answers are relatively short. We refer to Supplementary Notes 2 and 3 for ablations and experiments regarding our choice of entailment estimator for paragraph-length generations.

We implement two baselines. First, we implement a variant of the P (True) method, which is adapted to the new setting. For each factoid, we generate a question with answers in the same way as for semantic entropy. We then use the following prompt:

Question: {question} Here are some brainstormed ideas: {list of regenerated answers} Possible answer: {original answer} Is the possible answer true? Respond with “yes” or “no”.

As we cannot access the probabilities GPT-4 assigns to predicting ‘yes’ and ‘no’ as the next token, we approximate this using Monte Carlo samples. Concretely, we execute the above prompt ten times (at temperature 1) and then take the fraction of answers which was ‘yes’ as our unbiased Monte Carlo estimate of the token probability GPT-4 assigns to ‘yes’.

As a second, simpler, baseline we check if the model thinks the answer is true. We simply ask:

Following this text: {text so far} You see this statement: {proposition} Is it likely that the statement is true? Respond with ‘yes’ or ‘no’.

It is interesting that this method ought to perform very well if we think that the model has good ‘self-knowledge’ (that is, if “models mostly know what they don’t know” 24 ) but in fact semantic entropy is much better at detecting confabulations.

Data availability

The data used for the short-phrase and sentence-length generations are publicly available and the released code details how to access it. We release a public version of the FactualBio dataset as part of the code base for reproducing the paragraph-length experiments.

Code availability

We release all code used to produce the main experiments. The code for short-phrase and sentence-length experiments can be found at github.com/jlko/semantic_uncertainty and https://doi.org/10.5281/zenodo.10964366 (ref. 65 ). The code for paragraph-length experiments can be found at github.com/jlko/long_hallucinations and https://doi.org/10.5281/zenodo.10964366 (ref. 65 ).

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Acknowledgements

We thank G. Irving, K. Perlin, J. Richens, L. Rimell and M. Turpin for their comments or discussion related to this work. We thank K. Handa for his help with the human evaluation of our automated accuracy assessment. We thank F. Bickford Smith and L. Melo for their code review. Y.G. is supported by a Turing AI Fellowship funded by the UK government’s Office for AI, through UK Research and Innovation (grant reference EP/V030302/1), and delivered by the Alan Turing Institute.

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These authors contributed equally: Sebastian Farquhar, Jannik Kossen, Lorenz Kuhn

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OATML, Department of Computer Science, University of Oxford, Oxford, UK

Sebastian Farquhar, Jannik Kossen, Lorenz Kuhn & Yarin Gal

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S.F. led the work from conception to completion and proposed using bidirectional entailment to cluster generations as a way of computing entropy in LLMs. He wrote the main text, most of the Methods and Supplementary Information and prepared most of the figures. J.K. improved the mathematical formalization of semantic entropy; led the extension of semantic entropy to sentence- and paragraph-length generations; wrote the code for, and carried out, all the experiments and evaluations; wrote much of the Methods and Supplementary Information and prepared drafts of many figures; and gave critical feedback on the main text. L.K. developed the initial mathematical formalization of semantic entropy; wrote code for, and carried out, the initial experiments around semantic entropy and its variants which demonstrated the promise of the idea and helped narrow down possible research avenues to explore; and gave critical feedback on the main text. Y.G. ideated the project, proposing the idea to differentiate semantic and syntactic diversity as a tool for detecting hallucinations, provided high-level guidance on the research and gave critical feedback on the main text; he runs the research laboratory in which the work was carried out.

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Correspondence to Sebastian Farquhar .

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S.F. is currently employed by Google DeepMind and L.K. by OpenAI. For both, this paper was written under their University of Oxford affiliation. The remaining authors declare no competing interests.

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Extended data figures and tables

Extended data fig. 1 algorithm outline for bidirectional entailment clustering..

Given a set of outputs in response to a context, the bidirectional entailment answer returns a set of sets of outputs which have been classified as sharing a meaning.

Supplementary information

Supplementary information.

Supplementary Notes 1–7, Figs. 1–10, Tables 1–4 and references. Includes, worked example for semantic entropy calculation, discussion of limitations and computational cost of entailment clustering, ablation of entailment prediction and clustering methods, discussion of automated accuracy assessment, unaggregated results for sentence-length generations and further results for short-phrase generations.

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Farquhar, S., Kossen, J., Kuhn, L. et al. Detecting hallucinations in large language models using semantic entropy. Nature 630 , 625–630 (2024). https://doi.org/10.1038/s41586-024-07421-0

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DOI : https://doi.org/10.1038/s41586-024-07421-0

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