Reasoning Paths Optimization: Learning to Reason and Explore From Diverse Paths

Language models are few-shot learners

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Program synthesis with large language models

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Evaluating large language models trained on code

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Large language models are zero-shot reasoners

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Show your work: Scratchpads for intermediate computation with language models

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Training language models to follow instructions with human feedback

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Solving math word problems with process- and outcome-based feedback

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Jonathan Uesato, Nate Kushman, Ramana Kumar, Francis Song, Noah Siegel, L. Wang, Antonia Creswell, Geoffrey Irving, and Irina Higgins. 2022 · 2022

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Chain of thought prompting elicits reasoning in large language models

Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, brian ichter, Fei Xia, Ed H. Chi, Quoc V Le, and Denny Zhou. 2022 · 2022

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A general theoretical paradigm to understand learning from human preferences

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Mohammad Gheshlaghi Azar, Mark Rowland, Bilal Piot, Daniel Guo, Daniele Calandriello, Michal Valko, and Rémi Munos. 2023 · 2023

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Contrastive chain-of-thought prompting

Self-evaluation guided beam search for reasoning

Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, Xu Zhao, Min-Yen Kan, Junxian He, and Qizhe Xie. 2023 · 2023

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Secrets of rlhf in large language models part i: Ppo

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Rui Zheng, Shihan Dou, Songyang Gao, Yuan Hua, Wei Shen, Binghai Wang, Yan Liu, Senjie Jin, Qin Liu, Yuhao Zhou, et al. 2023 · 2023

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Llemma: An open language model for mathematics

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Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, Marco Dos Santos, Stephen McAleer, Albert Q. Jiang, Jia Deng, Stella Biderman, and Sean Welleck. 2024 · 2024

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InstructEval: Towards holistic evaluation of instruction-tuned large language models

Yew Ken Chia, Pengfei Hong, Lidong Bing, and Soujanya Poria. 2024a · 2024

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PuzzleVQA: Diagnosing multimodal reasoning challenges of language models with abstract visual patterns

Yew Ken Chia, Vernon Toh, Deepanway Ghosal, Lidong Bing, and Soujanya Poria. 2024b · 2024