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Chain-of-Thought (CoT) prompting can effectively elicit complex multi-step reasoning from Large Language Models~(LLMs).
Label-only membership inference attacks
Christopher A. Choquette-Choo, Florian Tramèr, Nicholas Carlini, and Nicolas Papernot. 2021 · 1974
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Imagenet: A large-scale hierarchical image database
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Membership inference attacks against machine learning models
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov. 2017 · 2017
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LOGAN: membership inference attacks against generative models
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Ml-leaks: Model and data independent membership inference attacks and defenses on machine learning models
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Wei Wang, Vincent W Zheng, Han Yu, and Chunyan Miao. 2019 · 2019
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Training verifiers to solve math word problems
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Chain of thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed Chi, Quoc Le, and Denny Zhou. 2022 · 2022
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Enhanced membership inference attacks against machine learning models
Jiayuan Ye, Aadyaa Maddi, Sasi Kumar Murakonda, Vincent Bindschaedler, and Reza Shokri. 2022 · 2022
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Star: Bootstrapping reasoning with reasoning
Eric Zelikman, Yuhuai Wu, and Noah D. Goodman. 2022 · 2022
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Least-to-most prompting enables complex reasoning in large language models
Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Olivier Bousquet, Quoc Le, and Ed Chi. 2022 · 2022
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Arkil Patel, Satwik Bhattamishra, and Navin Goyal. 2021 · 2021
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Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
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On the advance of making language models better reasoners
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Training language models to follow instructions with human feedback
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
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Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, and Denny Zhou. 2022 · 2022
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