‘GPT-3 nonfiction’ directory

Annotations sorted by machine learning into inferred 'tags'. This provides an alternative way to browse: instead of by date order, one can browse in topic order. The 'sorted' list has been automatically clustered into multiple sections & auto-labeled for easier browsing.

Beginning with the newest annotation, it uses the embedding of each annotation to attempt to create a list of nearest-neighbor annotations, creating a progression of topics. For more details, see the link.

Miscellaneous

Bibliography

2025-johri.pdf: “An Evaluation Framework for Clinical Use of Large Language Models in Patient Interaction Tasks”, Shreya Johri, Jaehwan Jeong, Benjamin A. Tran, Daniel I. Schlessinger, Shannon Wongvibulsin, Leandra A. Barnes, Hong-Yu Zhou, Zhuo Ran Cai, Eliezer M. Van Allen, David Kim, Roxana Daneshjou, Pranav Rajpurkar

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https://arxiv.org/abs/2410.13691: “Jailbreaking LLM-Controlled Robots”, Alexander Robey, Zachary Ravichandran, Vijay Kumar, Hamed Hassani, George J. Pappas

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https://arxiv.org/abs/2410.13893: “Can LLMs Be Scammed? A Baseline Measurement Study”, Udari Madhushani Sehwag, Kelly Patel, Francesca Mosca, Vineeth Ravi, Jessica Staddon

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https://arxiv.org/abs/2406.18518#salesforce: “APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets”, Zuxin Liu, Thai Hoang, Jianguo Zhang, Ming Zhu, Tian Lan, Shirley Kokane, Juntao Tan, Weiran Yao, Zhiwei Liu, Yihao Feng, Rithesh Murthy, Liangwei Yang, Silvio Savarese, Juan Carlos Niebles, Huan Wang, Shelby Heinecke, Caiming Xiong

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https://arxiv.org/abs/2406.07882: “Designing a Dashboard for Transparency and Control of Conversational AI”, Yida Chen, Aoyu Wu, Trevor DePodesta, Catherine Yeh, Kenneth Li, Nicholas Castillo Marin, Oam Patel, Jan Riecke, Shivam Raval, Olivia Seow, Martin Wattenberg, Fernanda Viégas

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https://www.sciencedirect.com/science/article/pii/S2666920X24000109: “Do Teachers Spot AI? Evaluating the Detectability of AI-Generated Texts among Student Essays”, Johanna Fleckenstein, Jennifer Meyer, Thorben Jansen, Stefan D. Keller, Olaf Köller, Jens Möller

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https://arxiv.org/abs/2405.18870#google: “LLMs Achieve Adult Human Performance on Higher-Order Theory of Mind Tasks”, Winnie Street, John Oliver Siy, Geoff Keeling, Adrien Baranes, Benjamin Barnett, Michael McKibben, Tatenda Kanyere, Alison Lentz, Blaise Aguera y Arcas, Robin I. M. Dunbar

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https://arxiv.org/abs/2403.18624: “Vulnerability Detection With Code Language Models: How Far Are We?”, Yangruibo Ding, Yanjun Fu, Omniyyah Ibrahim, Chawin Sitawarin, Xinyun Chen, Basel Alomair, David Wagner, Baishakhi Ray, Yizheng Chen

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https://www.wired.com/story/fast-forward-nsa-warns-us-adversaries-private-data-ai-edge/: “The NSA Warns That US Adversaries Free to Mine Private Data May Have an AI Edge: Gilbert Herrera, Who Leads Research at the National Security Agency, Says Large Language Models Are Incredibly Useful—And a Bit of a Headache—For America’s Intelligence Machine”, Will Knight

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https://arxiv.org/abs/2402.19450: “Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning Gap”, Saurabh Srivastava, Annarose M. B, Anto P. V, Shashank Menon, Ajay Sukumar, Adwaith Samod T, Alan Philipose, Stevin Prince, Sooraj Thomas

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https://arxiv.org/abs/2402.14903: “Tokenization Counts: the Impact of Tokenization on Arithmetic in Frontier LLMs”, Aaditya K. Singh, D. J. Strouse

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https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4602944: “Who Is AI Replacing? The Impact of Generative AI on Online Freelancing Platforms”, Ozge Demirci, Jonas Hannane, Xinrong Zhu

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https://arxiv.org/abs/2402.11753: “ArtPrompt: ASCII Art-Based Jailbreak Attacks against Aligned LLMs”, Fengqing Jiang, Zhangchen Xu, Luyao Niu, Zhen Xiang, Bhaskar Ramasubramanian, Bo Li, Radha Poovendran

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https://arxiv.org/abs/2310.08678: “Can GPT Models Be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on Mock CFA Exams”, Ethan Callanan, Amarachi Mbakwe, Antony Papadimitriou, Yulong Pei, Mathieu Sibue, Xiaodan Zhu, Zhiqiang Ma, Xiaomo Liu, Sameena Shah

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https://arxiv.org/abs/2310.06213: “GeoLLM: Extracting Geospatial Knowledge from Large Language Models”, Rohin Manvi, Samar Khanna, Gengchen Mai, Marshall Burke, David Lobell, Stefano Ermon

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2023-phillips.pdf: “Can a Computer Outfake a Human [Personality]?”, Jane Phillips, Chet Robie

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https://arxiv.org/abs/2310.04406: “Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models”, Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman, Haohan Wang, Yu-Xiong Wang

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https://arxiv.org/abs/2309.12269: “The Cambridge Law Corpus: A Corpus for Legal AI Research”, Andreas Östling, Holli Sargeant, Huiyuan Xie, Ludwig Bull, Alexander Terenin, Leif Jonsson, Måns Magnusson, Felix Steffek

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https://arxiv.org/abs/2309.00667: “Taken out of Context: On Measuring Situational Awareness in LLMs”, Lukas Berglund, Asa Cooper Stickland, Mikita Balesni, Max Kaufmann, Meg Tong, Tomasz Korbak, Daniel Kokotajlo, Owain Evans

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2024-banker.pdf: “Machine-Assisted Social Psychology Hypothesis Generation”, Sachin Banker, Promothesh Chatterjee, Himanshu Mishra, Arul Mishra

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https://arxiv.org/abs/2307.06439#microsoft: “Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events”, Yu Gu, Sheng Zhang, Naoto Usuyama, Yonas Woldesenbet, Cliff Wong, Praneeth Sanapathi, Mu Wei, Naveen Valluri, Erika Strandberg, Tristan Naumann, Hoifung Poon

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https://arxiv.org/abs/2307.05300#microsoft: “Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration”, Zhenhailong Wang, Shaoguang Mao, Wenshan Wu, Tao Ge, Furu Wei, Heng Ji

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https://arxiv.org/abs/2308.01404: “Hoodwinked: Deception and Cooperation in a Text-Based Game for Language Models”, Aidan O’Gara

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https://arxiv.org/abs/2306.15448: “Understanding Social Reasoning in Language Models With Language Models”, Kanishk Gandhi, Jan-Philipp Fränken, Tobias Gerstenberg, Noah D. Goodman

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https://arxiv.org/abs/2305.15717: “The False Promise of Imitating Proprietary LLMs”, Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, Dawn Song

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https://arxiv.org/abs/2305.13534: “How Language Model Hallucinations Can Snowball”, Muru Zhang, Ofir Press, William Merrill, Alisa Liu, Noah Smith

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https://www.medrxiv.org/content/10.1101/2023.03.24.23287731.full: “Performance of ChatGPT on Free-Response, Clinical Reasoning Exams”, Eric Strong, Alicia DiGiammarino, Yingjie Weng, Preetha Basaviah, Poonam Hosamani, Andre Kumar, Andrew Nevins, John Kugler, Jason Hom, Jonathan H. Chen

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https://arxiv.org/abs/2304.02015#alibaba: “How Well Do Large Language Models Perform in Arithmetic Tasks?”, Zheng Yuan, Hongyi Yuan, Chuanqi Tan, Wei Wang, Songfang Huang

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https://arxiv.org/abs/2303.03846#google: “Larger Language Models Do In-Context Learning Differently”, Jerry Wei, Jason Wei, Yi Tay, Dustin Tran, Albert Webson, Yifeng Lu, Xinyun Chen, Hanxiao Liu, Da Huang, Denny Zhou, Tengyu Ma

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https://arxiv.org/abs/2302.06476: “Is ChatGPT a General-Purpose Natural Language Processing Task Solver?”, Chengwei Qin, Aston Zhang, Zhuosheng Zhang, Jiaao Chen, Michihiro Yasunaga, Diyi Yang

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2023-kolt.pdf: “Predicting Consumer Contracts [With GPT-3]”, Noam Kolt

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https://www.vice.com/en/article/k7bdmv/judge-used-chatgpt-to-make-court-decision: “A Judge Just Used ChatGPT to Make a Court Decision: The Case Is the First Time a Court Has Admitted to Using the AI Text Generator’s Answers in a Legal Ruling”, Janus Rose

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https://arxiv.org/abs/2302.00560: “Co-Writing With Opinionated Language Models Affects Users’ Views”, Maurice Jakesch, Advait Bhat, Daniel Buschek, Lior Zalmanson, Mor Naaman

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https://nunosempere.com/blog/2023/01/11/can-gpt-produce-ideas/#if-you-never-miss-a-plane: “Can GPT-3 Produce New Ideas? Partially Automating Robin Hanson and Others § If You Never Miss a Plane…”, Nuño Sempere

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https://mededu.jmir.org/2023/1/e45312/: “How Does ChatGPT Perform on the United States Medical Licensing Examination? The Implications of Large Language Models for Medical Education and Knowledge Assessment”, Aidan Gilson, Conrad W. Safranek, Thomas Huang, Vimig Socrates, Ling Chi, Richard Andrew Taylor, David Chartash

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https://arxiv.org/abs/2212.14402: “GPT-3 Takes the Bar Exam”, Michael Bommarito II, Daniel Martin Katz

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https://arxiv.org/abs/2212.10496: “Precise Zero-Shot Dense Retrieval without Relevance Labels”, Luyu Gao, Xueguang Ma, Jimmy Lin, Jamie Callan

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https://arxiv.org/abs/2212.10560: “Self-Instruct: Aligning Language Models With Self-Generated Instructions”, Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah Smith, Daniel Khashabi, Hannaneh Hajishirzi

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https://techcrunch.com/2022/11/23/harvey-which-uses-ai-to-answer-legal-questions-lands-cash-from-openai/: “Harvey, Which Uses AI to Answer Legal Questions, Lands Cash from OpenAI”, Kyle Wiggers

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https://arxiv.org/abs/2210.03350#allen: “Self-Ask: Measuring and Narrowing the Compositionality Gap in Language Models (Bamboogle)”, Ofir Press, Muru Zhang, Sewon Min, Ludwig Schmidt, Noah A. Smith, Mike Lewis

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https://content.iospress.com/articles/argument-and-computation/aac210026: “How Persuasive Is AI-Generated Argumentation? An Analysis of the Quality of an Argumentative Text Produced by the GPT-3 AI Text Generator”, Martin Hinton, Jean H. M. Wagemans

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https://arxiv.org/abs/2209.03320: “What Does a Platypus Look Like? Generating Customized Prompts for Zero-Shot Image Classification (CuPL)”, Sarah Pratt, Rosanne Liu, Ali Farhadi

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2022-gpt3.pdf#page=2: “Can GPT-3 Write an Academic Paper on Itself, With Minimal Human Input?”, GPT-3, Almira Osmanovic-Thunström, Steinn Steingrimsson

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https://arxiv.org/abs/2205.12910#allen: “NaturalProver: Grounded Mathematical Proof Generation With Language Models”, Sean Welleck, Jiacheng Liu, Ximing Lu, Hannaneh Hajishirzi, Yejin Choi

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https://arxiv.org/abs/2202.12837#facebook: “Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?”, Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, Luke Zettlemoyer

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https://arxiv.org/abs/2201.05320#allen: “CommonsenseQA 2.0: Exposing the Limits of AI through Gamification”, Alon Talmor, Ori Yoran, Ronan Le Bras, Chandra Bhagavatula, Yoav Goldberg, Yejin Choi, Jonathan Berant

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2022-tu.pdf: “Limits of Using Artificial Intelligence and GPT-3 in Patent Prosecution”, Sean Tu, Amy Cyphert, Sam Perl

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https://aclanthology.org/2021.mrqa-1.7.pdf: “What Can a Generative Language Model Answer About a Passage?”, Douglas Summers-Stay, Claire Bonial, Clare Voss

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https://arxiv.org/abs/2010.14701#openai: “Scaling Laws for Autoregressive Generative Modeling”, Tom Henighan, Jared Kaplan, Mor Katz, Mark Chen, Christopher Hesse, Jacob Jackson, Heewoo Jun, Tom B. Brown, Prafulla Dhariwal, Scott Gray, Chris Hallacy, Benjamin Mann, Alec Radford, Aditya A. Ramesh, Nick Ryder, Daniel M. Ziegler, John Schulman, Dario Amodei, Sam McCandlish

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https://arxiv.org/abs/2009.03300: “MMLU: Measuring Massive Multitask Language Understanding”, Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, Jacob Steinhardt

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