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1992. OFFICIAL ORDER of the COMMISSIONER OF INSURANCE of the STATE OF TEXAS: Adoption of Flesch Reading Ease Test (No. 92 - 0573). https://www.tdi.texas.gov/pubs/pc/pccpfaq.html.

2023. Florida Statutes Section 627.4145 - Readable Language In Insurance Policies.http://www.leg.state.fl.us/statutes/index.cfm?App_mode=Display_Statute&Search_String=&URL=0600-0699/0627/Sections/0627.4145.html.

Qingyao Ai, Ting Bai, Zhao Cao, Yi Chang, Jiawei Chen, Zhumin Chen, Zhiyong Cheng, Shoubin Dong, Zhicheng Dou, Fuli Feng, 2023. Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community. AI Open 4 (2023), 80–90.

Rodrigo AlarconLourdesAlarcon, Lourdes Moreno, and Paloma Martínez. 2020. Word-Sense disambiguation system for text readability. In Proceedings of the 9th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion. 147–152.

Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, Alessandro Cappelli, Ruxandra Cojocaru, Merouane Debbah, Etienne Goffinet, Daniel Heslow, Julien Launay, Quentin Malartic, Badreddine Noune, Baptiste Pannier, and Guilherme Penedo. 2023. Falcon-40B: an open large language model with state-of-the-art performance. (2023).

Rohan Anil, AndrewM Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, 2023. PaLM2 Technical Report. (2023). arxiv:2305.10403

Matthew Arnold, Rachel K.E. Bellamy, Michael Hind, Stephanie Houde, Sameep Mehta, Aleksandra Mojsilovic, Ravi Nair, KarthikeyanNatesan Ramamurthy, Darrell Reimer, Alexandra Olteanu, David Piorkowski, Jason Tsay, and KushR. Varshney. 2019. FactSheets: Increasing Trust in AI Services through Supplier’s Declarations of Conformity. arxiv:1808.07261

Akari Asai, Matt Gardner, and Hannaneh Hajishirzi. 2022. Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks. arxiv:2112.08688

Yuntao Bai, Andy Jones, Kamal Ndousse, Amanda Askell, Anna Chen, Nova DasSarma, Dawn Drain, Stanislav Fort, Deep Ganguli, Tom Henighan, Nicholas Joseph, Saurav Kadavath, Jackson Kernion, Tom Conerly, Sheer El-Showk, Nelson Elhage, Zac Hatfield-Dodds, Danny Hernandez, Tristan Hume, Scott Johnston, Shauna Kravec, Liane Lovitt, Neel Nanda, Catherine Olsson, Dario Amodei, Tom Brown, Jack Clark, Sam McCandlish, Chris Olah, Ben Mann, and Jared Kaplan. 2022. Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback. arxiv:2204.05862

Alan Bailin and Ann Grafstein. 2016. Readability: Text and context. Springer.

Aparna Balagopalan, AbigailZ. Jacobs, and AsiaJ. Biega. 2023. The Role of Relevance in Fair Ranking. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR ’23).

Solon Barocas, AsiaJ. Biega, Benjamin Fish, Jundefineddrzej Niklas, and Luke Stark. 2020. When Not to Design, Build, or Deploy. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency(FAT* ’20).

EmilyM. Bender and Batya Friedman. 2018. Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science. Transactions of the Association for Computational Linguistics 6 (2018).

EmilyM. Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021. On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency(FAccT ’21).

RebekahGeorge Benjamin. 2012. Reconstructing readability: Recent developments and recommendations in the analysis of text difficulty. Educational Psychology Review 24 (2012), 63–88.

Gerd Berget and Andrew MacFarlane. 2019. Experimental Methods in IIR: The Tension between Rigour and Ethics in Studies Involving Users with Dyslexia. In Proceedings of the 2019 Conference on Human Information Interaction and Retrieval(CHIIR ’19).

Gerd Berget and Andrew MacFarlane. 2020. What is known about the impact of impairments on information seeking and searching?Journal of the Association for Information Science and Technology 71, 5 (2020), 596–611.

Gerd Berget, Andrew MacFarlane, and Nils Pharo. 2021. Modelling the information seeking and searching behaviour of users with impairments: Are existing models applicable?Journal of Documentation 77, 2 (2021).

VikasL Bommineni, Sanaea Bhagwagar, Daniel Balcarcel, Vishal Bommineni, Christos Davazitkos, and Donald Boyer. 2023. Performance of ChatGPT on the MCAT: The Road to Personalized and Equitable Premedical Learning. medRxiv (2023).

MatthewD Carter, MariannaM Walker, Kevin O’Brien, and MonicaS Hough. 2019. The effects of text length on reading abilities in accelerated reading tasks. Speech, Language and Hearing 22, 2 (2019), 111–121.

Stephen Casper, Xander Davies, Claudia Shi, ThomasKrendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Wang, Samuel Marks, Charbel-Raphaël Segerie, Micah Carroll, Andi Peng, Phillip Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, EricJ. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Bıyık, Anca Dragan, David Krueger, Dorsa Sadigh, and Dylan Hadfield-Menell. 2023. Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. arxiv:2307.15217

J.S. Chall and E. Dale. 1995. Readability Revisited: The New Dale-Chall Readability Formula. Brookline Books.

Paul Christiano, Jan Leike, TomB. Brown, Miljan Martic, Shane Legg, and Dario Amodei. 2023. Deep reinforcement learning from human preferences. arxiv:1706.03741

Lynne Cole, Andrew MacFarlane, and George Buchanan. 2016. Does dyslexia present barriers to information literacy in an online environment? A pilot study. Library and Information Research 40, 123 (2016), 24–46.

Lynne Cole, Andrew MacFarlane, and Stephann Makri. 2020. More than words: the impact of memory on how undergraduates with dyslexia interact with information. In Proceedings of the 2020 Conference on Human Information Interaction and Retrieval. 353–357.

Meri Coleman and TaLin Liau. 1975. A computer readability formula designed for machine scoring.Journal of Applied Psychology 60 (1975).

Mike Conover, Matt Hayes, Ankit Mathur, Jianwei Xie, Jun Wan, Sam Shah, Ali Ghodsi, Patrick Wendell, Matei Zaharia, and Reynold Xin. 2023. Free Dolly: Introducing the World’s First Truly Open Instruction-Tuned LLM. https://www.databricks.com/blog/2023/04/12/dolly-first-open-commercially-viable-instruction-tuned-llm

Stephanie Cosentino, Jennifer Manly, and Dan Mungas. 2007. Do reading tests measure the same construct in multilingual and multiethnic elders?Journal of the International Neuropsychological Society: JINS 13, 2 (2007), 228.

Ben Cost. 2023. Married father commits suicide after encouragement by AI chatbot: widow. https://nypost.com/2023/03/30/married-father-commits-suicide-after-encouragement-by-ai-chatbot-widow/.

Edgar Dale and JeanneS. Chall. 1948. A Formula for Predicting Readability. Educational Research Bulletin 27 (1948).

Anubrata Das, Kunjan Mehta, and Matthew Lease. 2019. CobWeb: A Research Prototype for Exploring User Bias in Political Fact-Checking. arxiv:1907.03718

TerryC. Davis and MichaelS. Wolf. 2004. Health literacy: implications for family medicine. Family Medicine 36 (2004). Issue 8.

Erik Derner and Kristina Batistič. 2023. Beyond the Safeguards: Exploring the Security Risks of ChatGPT. arxiv:2305.08005

Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer. 2023. QLoRA: Efficient Finetuning of Quantized LLMs. arXiv preprint arXiv:2305.14314 (2023).

TeresaHafer Donald L.Rubin and Kevin Arata. 2000. Reading and listening to oral‐based versus literate‐based discourse. Communication Education 49, 2 (2000).

Hanze Dong, Wei Xiong, Deepanshu Goyal, Yihan Zhang, Winnie Chow, Rui Pan, Shizhe Diao, Jipeng Zhang, Kashun Shum, and Tong Zhang. 2023. RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment. arxiv:2304.06767

Shiri Dori-Hacohen and ScottA. Hale. 2022. Information Ecosystem Threats in Minoritized Communities: Challenges, Open Problems and Research Directions. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR ’22).

Shiri Dori-Hacohen, Roberto Montenegro, Fabricio Murai, ScottA. Hale, Keen Sung, Michela Blain, and Jennifer Edwards-Johnson. 2021. Fairness via AI: Bias Reduction in Medical Information. arxiv:2109.02202

Kawin Ethayarajh, Yejin Choi, and Swabha Swayamdipta. 2022. Understanding Dataset Difficulty with Math 1-Usable Information. In Proceedings of the 39th International Conference on Machine Learning.

Guglielmo fa*ggioli, Laura Dietz, Charles L.A. Clarke, Gianluca Demartini, Matthias Hagen, Claudia Hauff, Noriko Kando, Evangelos Kanoulas, Martin Potthast, Benno Stein, and Henning Wachsmuth. 2023. Perspectives on Large Language Models for Relevance Judgment. In Proceedings of the 2023 ACM SIGIR International Conference on Theory of Information Retrieval(ICTIR ’23).

Patrick Fernandes, Aman Madaan, Emmy Liu, António Farinhas, PedroHenrique Martins, Amanda Bertsch, José G.C. de Souza, Shuyan Zhou, Tongshuang Wu, Graham Neubig, and André F.T. Martins. 2023. Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation. arxiv:2305.00955

Emilio Ferrara. 2023. Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models. arxiv:2304.03738

Rudolf Flesch. 1948. A new readability yardstick. Journal of Applied Psychology (1948).

Fiona Fui-HoonNah, Ruilin Zheng, Jingyuan Cai, Keng Siau, and Langtao Chen. 2023. Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration., 277–304pages.

IsabelO Gallegos, RyanA Rossi, Joe Barrow, MdMehrab Tanjim, Sungchul Kim, Franck Dernoncourt, Tong Yu, Ruiyi Zhang, and NesreenK Ahmed. 2023. Bias and Fairness in Large Language Models: A Survey. arXiv preprint arXiv:2309.00770 (2023).

Deep Ganguli, Liane Lovitt, Jackson Kernion, Amanda Askell, Yuntao Bai, Saurav Kadavath, Ben Mann, Ethan Perez, Nicholas Schiefer, Kamal Ndousse, Andy Jones, Sam Bowman, Anna Chen, Tom Conerly, Nova DasSarma, Dawn Drain, Nelson Elhage, Sheer El-Showk, Stanislav Fort, Zac Hatfield-Dodds, Tom Henighan, Danny Hernandez, Tristan Hume, Josh Jacobson, Scott Johnston, Shauna Kravec, Catherine Olsson, Sam Ringer, Eli Tran-Johnson, Dario Amodei, Tom Brown, Nicholas Joseph, Sam McCandlish, Chris Olah, Jared Kaplan, and Jack Clark. 2022. Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned. arxiv:2209.07858

Sourojit Ghosh and Aylin Caliskan. 2023. ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings across Bengali and Five other Low-Resource Languages. arXiv preprint arXiv:2305.10510 (2023).

Amelia Glaese, Nat McAleese, Maja Trębacz, John Aslanides, Vlad Firoiu, Timo Ewalds, Maribeth Rauh, Laura Weidinger, Martin Chadwick, Phoebe Thacker, Lucy Campbell-Gillingham, Jonathan Uesato, Po-Sen Huang, Ramona Comanescu, Fan Yang, Abigail See, Sumanth Dathathri, Rory Greig, Charlie Chen, Doug Fritz, JaumeSanchez Elias, Richard Green, Soňa Mokrá, Nicholas Fernando, Boxi Wu, Rachel Foley, Susannah Young, Iason Gabriel, William Isaac, John Mellor, Demis Hassabis, Koray Kavukcuoglu, LisaAnne Hendricks, and Geoffrey Irving. 2022. Improving alignment of dialogue agents via targeted human judgements. arxiv:2209.14375

Michael Glass, Gaetano Rossiello, MdFaisalMahbub Chowdhury, Ankita Naik, Pengshan Cai, and Alfio Gliozzo. 2022. Re2G: Retrieve, Rerank, Generate. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.

Lina Gong, Jingxuan Zhang, Mingqiang Wei, Haoxiang Zhang, and Zhiqiu Huang. 2023. What Is the Intended Usage Context of This Model? An Exploratory Study of Pre-Trained Models on Various Model Repositories. ACM Trans. Softw. Eng. Methodol. 32, 3 (may 2023).

Michael Green. 2021. Why Don’t You Act Your Age?: Recognizing the Stereotypical 8-12 Year Old Searcher by Their Search Behavior. (2021).

Laurence Habib, Gerd Berget, FrodeEika Sandnes, Nick Sanderson, Philippe Kahn, Siri fa*gernes, and Ali Olcay. 2012. Dyslexic students in higher education and virtual learning environments: An exploratory study. Journal of Computer Assisted Learning 28, 6 (2012), 574–584.

KennethA. Harwood. 1955. I. Listenability and readability. Speech Monographs 22, 1 (1955).

Sebastian Hofstätter, Jiecao Chen, Karthik Raman, and Hamed Zamani. 2023. FiD-Light: Efficient and Effective Retrieval-Augmented Text Generation. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR ’23).

EdwardJ. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2022. LoRA: Low-Rank Adaptation of Large Language Models. In The Tenth International Conference on Learning Representations.

JosephMarvin Imperial and HarishTayyar Madabushi. 2023. Flesch or Fumble? Evaluating Readability Standard Alignment of Instruction-Tuned Language Models. arXiv preprint arXiv:2309.05454 (2023).

Itay Itzhak, Gabriel Stanovsky, Nir Rosenfeld, and Yonatan Belinkov. 2023. Instructed to Bias: Instruction-Tuned Language Models Exhibit Emergent Cognitive Bias. arxiv:2308.00225

JerryL. Johns and ThomasE. Wheat. 1984. Newspaper Readability: Two Crucial Factors. Journal of Reading 27, 5 (1984).

Lorna Kane, Joe Carthy, and John Dunnion. 2006. Readability applied to information retrieval. In European Conference on Information Retrieval. Springer, 523–526.

DanielMartin Katz, MichaelJames Bommarito, Shang Gao, and Pablo Arredondo. 2023. GPT-4 Passes the Bar Exam. https://ssrn.com/abstract=4389233. (15 3 2023).

JPeter Kincaid, RobertP FishburneJr, RichardL Rogers, and BradS Chissom. 1975. Derivation of new readability formulas (automated readability index, fog count and flesch reading ease formula) for navy enlisted personnel. (1975).

Anton Korinek. 2023. Exploring the impact of language models on cognitive automation with David Autor, ChatGPT, and Claude. (2023).

Birgit Kvikne and Gerd Berget. 2021. In search of trustworthy information: a qualitative study of the search behavior of people with dyslexia in Norway. Universal Access in the Information Society 20 (2021), 1–12.

Amelia Lake. 2022. Hidden in Plain Sight: The Secret Epidemic of Illiteracy in the United States. https://www.yalehrj.org/post/hidden-in-plain-sight-the-secret-epidemic-of-illiteracy-in-the-united-states. Yale Human Rights Journal (2022).

Ida Larsen-Ledet, Bhaskar Mitra, and Siân Lindley. 2022. Ethical and Social Considerations in Automatic Expert Identification and People Recommendation in Organizational Knowledge Management Systems. arxiv:2209.03819

Harrison Lee, Samrat Phatale, Hassan Mansoor, Kellie Lu, Thomas Mesnard, Colton Bishop, Victor Carbune, and Abhinav Rastogi. 2023. RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback. arxiv:2309.00267

Peter Lee. 2016. Learning from Tay’s introduction. https://blogs.microsoft.com/blog/2016/03/25/learning-tays-introduction/.

Timo Lenzner. 2014. Are readability formulas valid tools for assessing survey question difficulty?Sociological Methods & Research 43, 4 (2014), 677–698.

Bo Li, Peng Qi, Bo Liu, Shuai Di, Jingen Liu, Jiquan Pei, Jinfeng Yi, and Bowen Zhou. 2023. Trustworthy AI: From Principles to Practices. ACM Comput. Surv. 55, 9 (2023).

Ruohan Li, Jianxiang Li, Bhaskar Mitra, Fernando Diaz, and AsiaJ. Biega. 2022. Exposing Query Identification for Search Transparency. In Proceedings of the ACM Web Conference 2022(WWW ’22).

Gabrielle Kaili-May Liu. 2023. Perspectives on the Social Impacts of Reinforcement Learning with Human Feedback. arxiv:2303.02891

Ruibo Liu, Ruixin Yang, Chenyan Jia, Ge Zhang, Denny Zhou, AndrewM. Dai, Diyi Yang, and Soroush Vosoughi. 2023. Training Socially Aligned Language Models in Simulated Human Society.

Andrew MacFarlane, A Albrair, CR Marshall, and George Buchanan. 2012. Phonological working memory impacts on information searching: An investigation of dyslexia. In Proceedings of the 4th Information Interaction in Context Symposium. 27–34.

Eric Martínez. 2023. Re-Evaluating GPT-4’s Bar Exam Performance. https://ssrn.com/abstract=4441311. (18 5 2023).

G.Harry McLaughlin. 1969. SMOG Grading-a New Readability Formula. Journal of Reading 12, 8 (1969).

Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, InioluwaDeborah Raji, and Timnit Gebru. 2019. Model Cards for Model Reporting. In Proceedings of the Conference on Fairness, Accountability, and Transparency(FAT* ’19).

Emiliana Murgia, MariaSoledad Pera, Monica Landoni, and Theo Huibers. 2023. Children on ChatGPT Readability in an Educational Context: Myth or Opportunity?. In Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization. 311–316.

Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, Xu Jiang, Karl Cobbe, Tyna Eloundou, Gretchen Krueger, Kevin Button, Matthew Knight, Benjamin Chess, and John Schulman. 2022. WebGPT: Browser-assisted question-answering with human feedback.

Administration of William J.Clinton. 1998. Memorandum on Plain Language in Government Writing.

OpenAI. 2022. Introducing ChatGPT. https://openai.com/blog/chatgpt.

OpenAI. 2023. GPT-4 Technical Report. arxiv:2303.08774

Organization for Economic Cooperation and Development (OECD). 1999. Measuring Student Knowledge and Skills: A New Framework for Assessment. Author, Paris.

Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, CarrollL. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe. 2022. Training language models to follow instructions with human feedback. arxiv:2203.02155

Srishti Palani, Adam Fourney, Shane Williams, Kevin Larson, Irina Spiridonova, and MeredithRingel Morris. 2020. An eye tracking study of web search by people with and without dyslexia. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. 729–738.

Yaneth delRosario PaloVillegas, AndreaElena PomaredaVera, MaríaElena RojasZegarra, and MDolores Calero. 2020. Effectiveness of the “Mente Sana [Healthy Mind]” cognitive training program for older illiterate adults with mild cognitive impairment. Geriatrics 5, 2 (2020), 34.

KarlMagnus Petersson, Alexandra Reis, and Martin Ingvar. 2001. Cognitive processing in literate and illiterate subjects: A review of some recent behavioral and functional neuroimaging data. Scandinavian journal of psychology 42, 3 (2001), 251–267.

Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency(FAccT ’22).

Huachuan Qiu, Shuai Zhang, Anqi Li, Hongliang He, and Zhenzhong Lan. 2023. Latent Jailbreak: A Benchmark for Evaluating Text Safety and Output Robustness of Large Language Models. arxiv:2307.08487

Alec Radford, Jeffrey Wu, Dario Amodei, Daniela Amodei, Jack Clark, Miles Brundage, and Ilya Sutskever. 2019. Better language models and their implications. OpenAI blog 1, 2 (2019).

Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and PeterJ. Liu. 2020. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. Journal of Machine Learning Research 21, 140 (2020).

BobbyD. Rampey, MadelineGoodman Robert Finneganand, Leyla Mohadjer, Tom Krenzke, Jacquie Hogan, and Stephen Provasnik. 2016. Skills of U.S. Unemployed, Young, and Older Adults in Sharper Focus: Results from the Program for the International Assessment of Adult Competencies (PIAAC) 2012/2014: First Look. https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2016039rev.

L Revell. 1994. Understanding, identifying, and teaching the low-literacy patient. In Seminars in Perioperative Nursing, Vol.3. 168–171.

Anna Rogers, Matt Gardner, and Isabelle Augenstein. 2023. QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehension. ACM Comput. Surv. 55, 10 (2023).

Johnathan Rothwell. 2020. Assessing the Economic Gains of Eradicating Illiteracy Nationally and Regionally in the United States. https://www.barbarabush.org/wp-content/uploads/2020/09/BBFoundation_GainsFromEradicatingIlliteracy_9_8.pdf.

Kevin Schaul, SzuYu Chen, and Nitasha Tiku. 2023. Inside the secret list of websites that make AI like ChatGPT sound smart. https://www.washingtonpost.com/technology/interactive/2023/ai-chatbot-learning/. (19 4 2023).

John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017. Proximal Policy Optimization Algorithms. arxiv:1707.06347

Marilyn Schultz and H Lippman. 2002. Low literacy skills needn’t hinder care.RN 65, 4 (2002), 45–48.

RJ Senter and EdgarA Smith. 1967. Automated readability index. Technical Report. Technical report, DTIC document.

GovernmentDigital Service. 2023. Content design: planning, writing and managing content. https://www.gov.uk/guidance/content-design/writing-for-gov-uk.

MarcelaLima Silagi, VivianUrbanejo Romero, MairaOkada de Oliveira, EduardoSturzeneker Trés, Sonia MariaDozzi Brucki, Márcia Radanovic, and LeticiaLessa Mansur. 2021. Inference comprehension from reading in individuals with mild cognitive impairment. Acta Neurologica Belgica 121 (2021), 879–887.

Nisan Stiennon, Long Ouyang, Jeffrey Wu, Daniel Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and PaulF Christiano. 2020. Learning to summarize with human feedback. In Advances in Neural Information Processing Systems, Vol.33.

LaurenM. Stossel, Nora Segar, Peter Gliatto, Robert Fallar, and Reena Karani. 2012. Readability of Patient Education Materials Available at the Point of Care. Journal of General Internal Medicine 27 (9 2012). Issue 9.

HLee Swanson. 2012. Adults with reading disabilities: Converting a meta-analysis to practice. Journal of Learning disabilities 45, 1 (2012), 17–30.

Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and TatsunoriB. Hashimoto. 2023. Stanford Alpaca: An Instruction-following LLaMA model. https://github.com/tatsu-lab/stanford_alpaca.

Binod Thapa-Chhetry and Tia Keck. 2019. A Chrome app for improving reading comprehension of health information online for individuals with low health literacy. In 2019 IEEE/ACM 1st International Workshop on Software Engineering for Healthcare (SEH). IEEE, 57–64.

Paul Thomas, Seth Spielman, Nick Craswell, and Bhaskar Mitra. 2023. Large Language Models Can Accurately Predict Searcher Preferences. (September 2023). https://www.microsoft.com/en-us/research/publication/large-language-models-can-accurately-predict-searcher-preferences/

Tourism and the Centrefor Education StatisticsDivision. 2013. Skills in Canada: First Results from the Programme for the International Assessmentof Adult Competencies (PIAAC). http://www.cmec.ca/Publications/Lists/Publications/Attachments/315/Canadian-PIAAC-Report.EN.pdf.

Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023. LLaMA: Open and Efficient Foundation Language Models. arxiv:2302.13971

Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, CristianCanton Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, PunitSingh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, EricMichael Smith, Ranjan Subramanian, XiaoqingEllen Tan, Binh Tang, Ross Taylor, Adina Williams, JianXiang Kuan, Puxin Xu, Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurelien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom. 2023. Llama 2: Open Foundation and Fine-Tuned Chat Models. arxiv:2307.09288[cs.CL]

W3C. [n. d.]. Understanding WCAG 2.0: Reading Level: Understanding SC 3.1.5. https://www.w3.org/TR/UNDERSTANDING-WCAG20/meaning-supplements.html.

Shuai Wang, Harrisen Scells, Bevan Koopman, and Guido Zuccon. 2023. Can ChatGPT Write a Good Boolean Query for Systematic Review Literature Search?. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR ’23).

Shuai Wang, Harrisen Scells, Martin Potthast, Bevan Koopman, and Guido Zuccon. 2023. Generating Natural Language Queries for More Effective Systematic Review Screening Prioritisation. arxiv:2309.05238

Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, NoahA. Smith, Daniel Khashabi, and Hannaneh Hajishirzi. 2022. Self-Instruct: Aligning Language Model with Self Generated Instructions.

WillianMassami Watanabe. 2010. Facilita: reading assistance to the functionally illiterate. In Proceedings of the 2010 International Cross Disciplinary Conference on Web Accessibility (W4A). 1–2.

Jason Wei, Maarten Bosma, Vincent Zhao, Kelvin Guu, AdamsWei Yu, Brian Lester, Nan Du, AndrewM. Dai, and QuocV Le. 2022. Finetuned Language Models are Zero-Shot Learners. In International Conference on Learning Representations.

Minghao Wu and AlhamFikri Aji. 2023. Style over substance: Evaluation biases for large language models. arXiv preprint arXiv:2307.03025 (2023).

Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Sebastian Gehrmann, Prabhanjan Kambadur, David Rosenberg, and Gideon Mann. 2023. BloombergGPT: A Large Language Model for Finance. arxiv:2303.17564

Yachao Zhao, Bo Wang, Dongming Zhao, Kun Huang, Yan Wang, Ruifang He, and Yuexian Hou. 2023. Mind vs. Mouth: On Measuring Re-judge Inconsistency of Social Bias in Large Language Models. arxiv:2308.12578

Chunting Zhou, Pengfei Liu, Puxin Xu, Srini Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, Susan Zhang, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, and Omer Levy. 2023. LIMA: Less Is More for Alignment. arxiv:2305.11206

Andy Zou, Zifan Wang, J.Zico Kolter, and Matt Fredrikson. 2023. Universal and Transferable Adversarial Attacks on Aligned Language Models. arxiv:2307.15043