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Medical knowledge is context-dependent and requires consistent reasoning across various natural language expressions of semantically equivalent phrases.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B. Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. 2020 · 2001
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Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2021 · 2009
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Di Jin, Eileen Pan, Nassim Oufattole, Wei-Hung Weng, Hanyi Fang, and Peter Szolovits. 2020 · 2009
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Perceptions of and barriers to use of generic medications in a rural african american population, alabama, 2011
K. Sewell, S. Andreae, E. Luke, and M. M. Safford. 2012 · 2011
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Perceptions of generic medication in the general population, doctors and pharmacists: a systematic review
S. Colgan, K. Faasse, L. R. Martin, M. H. Stephens, A. Grey, and K. J. Petrie. 2015 · 2015
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PubMedQA: A dataset for biomedical research question answering
Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William Cohen, and Xinghua Lu. 2019 · 2019
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2019 · 2019
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Do imagenet classifiers generalize to imagenet?
Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, and Vaishaal Shankar. 2019 · 2019
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The pile: An 800gb dataset of diverse text for language modeling
Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, Shawn Presser, and Connor Leahy. 2020 · 2020
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Medmcqa : A large-scale multi-subject multi-choice dataset for medical domain question answering
Ankit Pal, Logesh Kumar Umapathi, and Malaikannan Sankarasubbu. 2022 · 2022
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Emergent abilities of large language models
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, and William Fedus. 2022 · 2022
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The future landscape of large language models in medicine
Jan Clusmann, Fiona R Kolbinger, Hannah Sophie Muti, Zunamys I Carrero, Jan-Niklas Eckardt, Narmin Ghaffari Laleh, Chiara Maria Lavinia Löffler, Sophie-Caroline Schwarzkopf, Michaela Unger, Gregory P Veldhuizen, et al. 2023 · 2023
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Redpajama: An open source recipe to reproduce llama training dataset
Together Computer. 2023 · 2023
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A framework for few-shot language model evaluation
Leo Gao, Jonathan Tow, Baber Abbasi, Stella Biderman, Sid Black, Anthony DiPofi, Charles Foster, Laurence Golding, Jeffrey Hsu, Alain Le Noac’h, Haonan Li, Kyle McDonell, Niklas Muennighoff, Chris Ociepa, Jason Phang, Laria Reynolds, Hailey Schoelkopf, Aviya Skowron, Lintang Sutawika, Eric Tang, Anish Thite, Ben Wang, Kevin Wang, and Andy Zou. 2023 · 2023
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Suriya Gunasekar, Yi Zhang, Jyoti Aneja, Caio César Teodoro Mendes, Allie Del Giorno, Sivakanth Gopi, Mojan Javaheripi, Piero Kauffmann, Gustavo de Rosa, Olli Saarikivi, et al. 2023 · 2023
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Textbooks are all you need ii: phi-1.5
Yuanzhi Li, Sébastien Bubeck, Ronen Eldan, Allie Del Giorno, Suriya Gunasekar, and Yin Tat Lee. 2023 · 2023
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Benchmarking large language models on CMExam - a comprehensive chinese medical exam dataset
Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Zhu Lei, and Michael Lingzhi Li. 2023 · 2023
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Infini-gram: Scaling unbounded n-gram language models to a trillion tokens
Jiacheng Liu, Sewon Min, Luke Zettlemoyer, Yejin Choi, and Hannaneh Hajishirzi. 2024 · 2024
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Medfuzz: Exploring the robustness of large language models in medical question answering
Robert Osazuwa Ness, Katie Matton, Hayden Helm, Sheng Zhang, Junaid Bajwa, Carey E. Priebe, and Eric Horvitz. 2024 · 2024
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openlifescienceai open medical llm leaderboard
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Qwen2 technical report
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Detecting pretraining data from large language models
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alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Sheng Lu, Irina Bigoulaeva, Rachneet Sachdeva, Harish Tayyar Madabushi, and Iryna Gurevych. 2023 · 2023
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Paloma: A benchmark for evaluating language model fit
Ian Magnusson, Akshita Bhagia, Valentin Hofmann, Luca Soldaini, Ananya Harsh Jha, Oyvind Tafjord, Dustin Schwenk, Evan Pete Walsh, Yanai Elazar, Kyle Lo, Dirk Groeneveld, Iz Beltagy, Hannaneh Hajishirzi, Noah A. Smith, Kyle Richardson, and Jesse Dodge. 2023 · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
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Phi-3 technical report: A highly capable language model locally on your phone
Marah Abdin, Sam Ade Jacobs, Ammar Ahmad Awan, Jyoti Aneja, Ahmed Awadallah, Hany Awadalla, Nguyen Bach, Amit Bahree, Arash Bakhtiari, Harkirat Behl, et al. 2024 · 2024
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Llama 3 model card
AI@Meta. 2024 · 2024
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Aya 23: Open weight releases to further multilingual progress
Viraat Aryabumi, John Dang, Dwarak Talupuru, Saurabh Dash, David Cairuz, Hangyu Lin, Bharat Venkitesh, Madeline Smith, Kelly Marchisio, Sebastian Ruder, Acyr Locatelli, Julia Kreutzer, Nick Frosst, Phil Blunsom, Marzieh Fadaee, Ahmet Üstün, and Sara Hooker. 2024 · 2024
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Ai-generated clinical summaries require more than accuracy
Katherine E. Goodman, Paul H. Yi, and Daniel J. Morgan. 2024 · 2024
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Large language models to identify social determinants of health in electronic health records
Marco Guevara, Shan Chen, Spencer Thomas, Tafadzwa L. Chaunzwa, Idalid Franco, Benjamin Kann, Shalini Moningi, Jack Qian, Madeleine Goldstein, Susan Harper, Hugo JWL Aerts, Guergana K. Savova, Raymond H. Mak, and Danielle S. Bitterman. 2024 · 2024
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Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
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Functional benchmarks for robust evaluation of reasoning performance, and the reasoning gap
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Mmlu-pro: A more robust and challenging multi-task language understanding benchmark
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Benchmarking benchmark leakage in large language models
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Yi: Open foundation models by 01. ai
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Assessing the potential of gpt-4 to perpetuate racial and gender biases in health care: a model evaluation study
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A careful examination of large language model performance on grade school arithmetic
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Don’t make your llm an evaluation benchmark cheater
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