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of 4
pro vyhledávání: '"Umapathi, Logesh Kumar"'
This research paper focuses on the challenges posed by hallucinations in large language models (LLMs), particularly in the context of the medical domain. Hallucination, wherein these models generate plausible yet unverified or incorrect information,
Externí odkaz:
http://arxiv.org/abs/2307.15343
Autor:
Li, Raymond, Allal, Loubna Ben, Zi, Yangtian, Muennighoff, Niklas, Kocetkov, Denis, Mou, Chenghao, Marone, Marc, Akiki, Christopher, Li, Jia, Chim, Jenny, Liu, Qian, Zheltonozhskii, Evgenii, Zhuo, Terry Yue, Wang, Thomas, Dehaene, Olivier, Davaadorj, Mishig, Lamy-Poirier, Joel, Monteiro, João, Shliazhko, Oleh, Gontier, Nicolas, Meade, Nicholas, Zebaze, Armel, Yee, Ming-Ho, Umapathi, Logesh Kumar, Zhu, Jian, Lipkin, Benjamin, Oblokulov, Muhtasham, Wang, Zhiruo, Murthy, Rudra, Stillerman, Jason, Patel, Siva Sankalp, Abulkhanov, Dmitry, Zocca, Marco, Dey, Manan, Zhang, Zhihan, Fahmy, Nour, Bhattacharyya, Urvashi, Yu, Wenhao, Singh, Swayam, Luccioni, Sasha, Villegas, Paulo, Kunakov, Maxim, Zhdanov, Fedor, Romero, Manuel, Lee, Tony, Timor, Nadav, Ding, Jennifer, Schlesinger, Claire, Schoelkopf, Hailey, Ebert, Jan, Dao, Tri, Mishra, Mayank, Gu, Alex, Robinson, Jennifer, Anderson, Carolyn Jane, Dolan-Gavitt, Brendan, Contractor, Danish, Reddy, Siva, Fried, Daniel, Bahdanau, Dzmitry, Jernite, Yacine, Ferrandis, Carlos Muñoz, Hughes, Sean, Wolf, Thomas, Guha, Arjun, von Werra, Leandro, de Vries, Harm
The BigCode community, an open-scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder and StarCoderBase: 15.5B parameter models with 8K context length, infilling capabilitie
Externí odkaz:
http://arxiv.org/abs/2305.06161
Autor:
Allal, Loubna Ben, Li, Raymond, Kocetkov, Denis, Mou, Chenghao, Akiki, Christopher, Ferrandis, Carlos Munoz, Muennighoff, Niklas, Mishra, Mayank, Gu, Alex, Dey, Manan, Umapathi, Logesh Kumar, Anderson, Carolyn Jane, Zi, Yangtian, Poirier, Joel Lamy, Schoelkopf, Hailey, Troshin, Sergey, Abulkhanov, Dmitry, Romero, Manuel, Lappert, Michael, De Toni, Francesco, del Río, Bernardo García, Liu, Qian, Bose, Shamik, Bhattacharyya, Urvashi, Zhuo, Terry Yue, Yu, Ian, Villegas, Paulo, Zocca, Marco, Mangrulkar, Sourab, Lansky, David, Nguyen, Huu, Contractor, Danish, Villa, Luis, Li, Jia, Bahdanau, Dzmitry, Jernite, Yacine, Hughes, Sean, Fried, Daniel, Guha, Arjun, de Vries, Harm, von Werra, Leandro
The BigCode project is an open-scientific collaboration working on the responsible development of large language models for code. This tech report describes the progress of the collaboration until December 2022, outlining the current state of the Per
Externí odkaz:
http://arxiv.org/abs/2301.03988
Publikováno v:
ACM Conference on Health, Inference, and Learning (CHIL) 2022
This paper introduces MedMCQA, a new large-scale, Multiple-Choice Question Answering (MCQA) dataset designed to address real-world medical entrance exam questions. More than 194k high-quality AIIMS \& NEET PG entrance exam MCQs covering 2.4k healthca
Externí odkaz:
http://arxiv.org/abs/2203.14371