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Large language models (LLM) have achieved impressive performance on medical question-answering benchmarks.
Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
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Race/ethnicity in medical education: an analysis of a question bank for step 1 of the united states medical licensing examination
Kelsey Ripp and Lundy Braun · 2017
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Adversarially robust generalization requires more data
Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, and Aleksander Madry · 2018
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Robustness may be at odds with accuracy
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, and Aleksander Madry · 2018
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Pubmedqa: A dataset for biomedical research question answering
Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William W Cohen, and Xinghua Lu · 2019
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Language models are few-shot learners, 2020
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
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Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt · 2020
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Cognitive bias: how understanding its impact on antibiotic prescribing decisions can help advance antimicrobial stewardship
Bradley J Langford, Nick Daneman, Valerie Leung, and Dale J Langford · 2020
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Stereoset: Measuring stereotypical bias in pretrained language models
Moin Nadeem, Anna Bethke, and Siva Reddy · 2020
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Investigating gender bias in language models using causal mediation analysis
Jesse Vig, Sebastian Gehrmann, Yonatan Belinkov, Sharon Qian, Daniel Nevo, Yaron Singer, and Stuart Shieber · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander M. Rush · 2020
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Nbme item-writing guide, February 2021
Melissa S. Billings, Kristine DeRuchie, Kieran Hussie, Allison Kulesher, Jacquelyn Merrell, Amy Morales, Miguel A. Paniagua, Jennifer Sherlock, Kimberly A. Swygert, and Julie Tyson · 2021
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What disease does this patient have? a large-scale open domain question answering dataset from medical exams
Di Jin, Eileen Pan, Nassim Oufattole, Wei-Hung Weng, Hanyi Fang, and Peter Szolovits · 2021
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Ai and the everything in the whole wide world benchmark
Inioluwa Deborah Raji, Emily M Bender, Amandalynne Paullada, Emily Denton, and Alex Hanna · 2021
Cited alongside, same era.
Can large language models reason about medical questions?
Valentin Liévin, Christoffer Egeberg Hother, and Ole Winther · 2022
Cited alongside, same era.
Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering
Ankit Pal, Logesh Kumar Umapathi, and Malaikannan Sankarasubbu · 2022
Cited alongside, same era.
Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering
Ankit Pal, Logesh Kumar Umapathi, and Malaikannan Sankarasubbu · 2022
Cited alongside, same era.
Large language models propagate race-based medicine
Jesutofunmi A Omiye, Jenna C Lester, Simon Spichak, Veronica Rotemberg, and Roxana Daneshjou · 2023
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Towards expert-level medical question answering with large language models
Karan Singhal, Tao Tu, Juraj Gottweis, Rory Sayres, Ellery Wulczyn, Le Hou, Kevin Clark, Stephen Pfohl, Heather Cole-Lewis, Darlene Neal, et al · 2023
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Large language models in medicine
Arun James Thirunavukarasu, Darren Shu Jeng Ting, Kabilan Elangovan, Laura Gutierrez, Ting Fang Tan, and Daniel Shu Wei Ting · 2023
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Miles Turpin, Julian Michael, Ethan Perez, and Samuel R Bowman · 2023
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Self-consistency improves chain of thought reasoning in language models, 2023
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou · 2023
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Karan Singhal, Shekoofeh Azizi, Tao Tu, S Sara Mahdavi, Jason Wei, Hyung Won Chung, Nathan Scales, Ajay Tanwani, Heather Cole-Lewis, Stephen Pfohl, et al · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
Cited alongside, same era.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
Cited alongside, same era.
Jailbreaking black box large language models in twenty queries
Patrick Chao, Alexander Robey, Edgar Dobriban, Hamed Hassani, George J Pappas, and Eric Wong · 2023
Cited alongside, same era.
Meditron-70b: Scaling medical pretraining for large language models, 2023
Zeming Chen, Alejandro Hernández-Cano, Angelika Romanou, Antoine Bonnet, Kyle Matoba, Francesco Salvi, Matteo Pagliardini, Simin Fan, Andreas Köpf, Amirkeivan Mohtashami, Alexandre Sallinen, Alireza Sakhaeirad, Vinitra Swamy, Igor Krawczuk, Deniz Bayazit, Axel Marmet, Syrielle Montariol, Mary-Anne Hartley, Martin Jaggi, and Antoine Bosselut · 2023
Cited alongside, same era.
Causal reasoning and large language models: Opening a new frontier for causality
Emre Kıcıman, Robert Osazuwa Ness, Amit Sharma, and Chenhao Tan · 2023
Cited alongside, same era.
Publicly shareable clinical large language model built on synthetic clinical notes
Sunjun Kweon, Junu Kim, Jiyoun Kim, Sujeong Im, Eunbyeol Cho, Seongsu Bae, Jungwoo Oh, Gyubok Lee, Jong Hak Moon, Seng Chan You, et al · 2023
Cited alongside, same era.
Capabilities of gpt-4 on medical challenge problems
Harsha Nori, Nicholas King, Scott Mayer McKinney, Dean Carignan, and Eric Horvitz · 2023
Cited alongside, same era.
Later among the works it cites.
Large language models as optimizers
Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V Le, Denny Zhou, and Xinyun Chen · 2023
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Universal and transferable adversarial attacks on aligned language models
Andy Zou, Zifan Wang, J Zico Kolter, and Matt Fredrikson · 2023
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https://github.com/guidance-ai/guidance , 2024
A guidance language for controlling large language models · 2024
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Openbiollms: Advancing open-source large language models for healthcare and life sciences
Malaikannan Sankarasubbu Ankit Pal · 2024
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Biomistral: A collection of open-source pretrained large language models for medical domains, 2024
Yanis Labrak, Adrien Bazoge, Emmanuel Morin, Pierre-Antoine Gourraud, Mickael Rouvier, and Richard Dufour · 2024
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The open medical-llm leaderboard: Benchmarking large language models in healthcare, April 2024
Aaditya Ura, Pasquale Minervini, and Clémentine Fourrier · 2024
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Assessing the potential of gpt-4 to perpetuate racial and gender biases in health care: a model evaluation study
Travis Zack, Eric Lehman, Mirac Suzgun, Jorge A Rodriguez, Leo Anthony Celi, Judy Gichoya, Dan Jurafsky, Peter Szolovits, David W Bates, Raja-Elie E Abdulnour, et al · 2024
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