Reverse Thinking Makes LLMs Stronger Reasoners

Boolq: Exploring the surprising difficulty of natural yes/no questions

Original

Christopher Clark, Kenton Lee, Ming-Wei Chang, Tom Kwiatkowski, Michael Collins, and Kristina Toutanova. 2019 · 1905

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Model compression

Cristian Buciluǎ, Rich Caruana, and Alexandru Niculescu-Mizil. 2006 · 2006

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Distilling the knowledge in a neural network

Original

Geoffrey Hinton, Oriol Vinyals, and Jeff Dean. 2015 · 2015

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Dual learning for machine translation

Di He, Yingce Xia, Tao Qin, Liwei Wang, Nenghai Yu, Tie-Yan Liu, and Wei-Ying Ma. 2016 · 2016

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Improving neural machine translation models with monolingual data

Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016

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Question answering and question generation as dual tasks

Original

Duyu Tang, Nan Duan, Tao Qin, Zhao Yan, and Ming Zhou. 2017 · 2017

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Learning from multiple teacher networks

Shan You, Chang Xu, Chao Xu, and Dacheng Tao. 2017 · 2017

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e-snli: Natural language inference with natural language explanations

Oana-Maria Camburu, Tim Rocktäschel, Thomas Lukasiewicz, and Phil Blunsom. 2018 · 2018

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Think you have solved question answering? try arc, the ai2 reasoning challenge

Original

Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, and Oyvind Tafjord. 2018 · 2018

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Can a suit of armor conduct electricity? a new dataset for open book question answering

Todor Mihaylov, Peter Clark, Tushar Khot, and Ashish Sabharwal. 2018 · 2018

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NEXUS network: Connecting the preceding and the following in dialogue generation

Xiaoyu Shen, Hui Su, Wenjie Li, and Dietrich Klakow. 2018 · 2018

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Model-level dual learning

Yingce Xia, Xu Tan, Fei Tian, Tao Qin, Nenghai Yu, and Tie-Yan Liu. 2018 · 2018

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CommonsenseQA: A question answering challenge targeting commonsense knowledge

Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant. 2019 · 2019

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Big self-supervised models are strong semi-supervised learners

Original

Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, and Geoffrey E Hinton. 2020 · 2020

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Adversarial NLI: A new benchmark for natural language understanding

Yixin Nie, Adina Williams, Emily Dinan, Mohit Bansal, Jason Weston, and Douwe Kiela. 2020 · 2020

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Opposites in reasoning processes: Do we use them more than we think, but less than we could?

Erika Branchini, Elena Capitani, Roberto Burro, Ugo Savardi, and Ivana Bianchi. 2021 · 2021

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Training verifiers to solve math word problems

Original

Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, et al. 2021 · 2021

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Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies

Mor Geva, Daniel Khashabi, Elad Segal, Tushar Khot, Dan Roth, and Jonathan Berant. 2021 · 2021

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Measuring mathematical problem solving with the math dataset

Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt. 2021 · 2021

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Stylized dialogue generation with multi-pass dual learning

Jinpeng Li, Yingce Xia, Rui Yan, Hongda Sun, Dongyan Zhao, and Tie-Yan Liu. 2021 · 2021

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LoRA: Low-rank adaptation of large language models

Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2022 · 2022

Cited alongside, same era.

Large language models are zero-shot reasoners

Takeshi Kojima, Shixiang (Shane) Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022

Cited alongside, same era.

Solving quantitative reasoning problems with language models

Aitor Lewkowycz, Anders Andreassen, David Dohan, Ethan Dyer, Henryk Michalewski, Vinay Ramasesh, Ambrose Slone, Cem Anil, Imanol Schlag, Theo Gutman-Solo, et al. 2022 · 2022

Cited alongside, same era.

Teaching small language models to reason

Original

Lucie Charlotte Magister, Jonathan Mallinson, Jakub Adamek, Eric Malmi, and Aliaksei Severyn. 2022 · 2022

Cited alongside, same era.

Self-consistency improves chain of thought reasoning in language models

Original

Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2022 · 2022

Dynamic prompt learning via policy gradient for semi-structured mathematical reasoning

Pan Lu, Liang Qiu, Kai-Wei Chang, Ying Nian Wu, Song-Chun Zhu, Tanmay Rajpurohit, Peter Clark, and Ashwin Kalyan. 2023 · 2023

Later among the works it cites.

Envisioning future from the past: Hierarchical duality learning for multi-turn dialogue generation

Ang Lv, Jinpeng Li, Shufang Xie, and Rui Yan. 2023 · 2023

Later among the works it cites.

Orca 2: Teaching small language models how to reason

Original

Arindam Mitra, Luciano Del Corro, Shweti Mahajan, Andres Codas, Clarisse Simoes, Sahaj Agarwal, Xuxi Chen, Anastasia Razdaibiedina, Erik Jones, Kriti Aggarwal, et al. 2023 · 2023

Later among the works it cites.

Orca: Progressive learning from complex explanation traces of gpt-4

Original

Subhabrata Mukherjee, Arindam Mitra, Ganesh Jawahar, Sahaj Agarwal, Hamid Palangi, and Ahmed Awadallah. 2023 · 2023

Later among the works it cites.

Unleashing the emergent cognitive synergy in large language models: A task-solving agent through multi-persona self-collaboration