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Despite their strengths, large language models (LLMs) often fail to communicate their confidence accurately, making it difficult to assess when they might be wrong and limiting their reliability.
Verification of forecasts expressed in terms of probability
Glenn W Brier · 1950
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Andrew P Bradley · 1997
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On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger · 2017
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Chain-of-thought prompting elicits reasoning in large language models
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Vaishnavi Shrivastava, Percy Liang, and Ananya Kumar · 2023
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Katherine Tian, Eric Mitchell, Allan Zhou, Archit Sharma, Rafael Rafailov, Huaxiu Yao, Chelsea Finn, and Christopher Manning · 2023
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Neeraj Varshney, Wenlin Yao, Hongming Zhang, Jianshu Chen, and Dong Yu · 2023
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Language model cascades: Token-level uncertainty and beyond
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