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We introduce STREET, a unified multi-task and multi-domain natural language reasoning and explanation benchmark.
Explain yourself! leveraging language models for commonsense reasoning
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A survey of artificial cognitive systems: Implications for the autonomous development of mental capabilities in computational agents
David Vernon, Giorgio Metta, and Giulio Sandini · 2007
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An exact graph edit distance algorithm for solving pattern recognition problems
Zeina Abu-Aisheh, Romain Raveaux, Jean-Yves Ramel, and Patrick Martineau · 2015
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning · 2015
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Simpler context-dependent logical forms via model projections
Reginald Long, Panupong Pasupat, and Percy Liang · 2016
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Program induction by rationale generation: Learning to solve and explain algebraic word problems
Wang Ling, Dani Yogatama, Chris Dyer, and Phil Blunsom · 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
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Think you have solved question answering? try arc, the ai2 reasoning challenge
Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, and Oyvind Tafjord · 2018
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WorldTree: A corpus of explanation graphs for elementary science questions supporting multi-hop inference
Peter Jansen, Elizabeth Wainwright, Steven Marmorstein, and Clayton Morrison · 2018
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GLUE: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel Bowman · 2018
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A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel Bowman · 2018
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Hotpotqa: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W Cohen, Ruslan Salakhutdinov, and Christopher D Manning · 2018
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SWAG: A large-scale adversarial dataset for grounded commonsense inference
Rowan Zellers, Yonatan Bisk, Roy Schwartz, and Yejin Choi · 2018
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DROP: A reading comprehension benchmark requiring discrete reasoning over paragraphs
Dheeru Dua, Yizhong Wang, Pradeep Dasigi, Gabriel Stanovsky, Sameer Singh, and Matt Gardner · 2019
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Attention is not Explanation
Sarthak Jain and Byron C. Wallace · 2019
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu · 2020
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Bleurt: Learning robust metrics for text generation
Thibault Sellam, Dipanjan Das, and Ankur P Parikh · 2020
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Open question answering over tables and text
Wenhu Chen, Ming-Wei Chang, Eva Schlinger, William Yang Wang, and William W. Cohen · 2021
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Training verifiers to solve math word problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman · 2021
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Explaining answers with entailment trees
Bhavana Dalvi, Peter Jansen, Oyvind Tafjord, Zhengnan Xie, Hannah Smith, Leighanna Pipatanangkura, and Peter Clark · 2021
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Ilya Loshchilov and Frank Hutter · 2019
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Predicting state changes in procedural text using analogical question answering
Danilo Ribeiro, Thomas Hinrichs, Maxwell Crouse, Kenneth Forbus, Maria Chang, and Michael Witbrock · 2019
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CLUTRR: A diagnostic benchmark for inductive reasoning from text
Koustuv Sinha, Shagun Sodhani, Jin Dong, Joelle Pineau, and William L. Hamilton · 2019
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Superglue: A stickier benchmark for general-purpose language understanding systems
Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel Bowman · 2019
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Generating rationales in visual question answering
Hammad A. Ayyubi, Md. Mehrab Tanjim, Julian McAuley, and G. Cottrell · 2020
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
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Evaluation of text generation: A survey
Asli Celikyilmaz, Elizabeth Clark, and Jianfeng Gao · 2020
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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
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Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt · 2021
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Combining analogy with language models for knowledge extraction
Danilo Neves Ribeiro and Kenneth Forbus · 2021
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ProofWriter: Generating implications, proofs, and abductive statements over natural language
Oyvind Tafjord, Bhavana Dalvi, and Peter Clark · 2021
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Do multi-hop question answering systems know how to answer the single-hop sub-questions?
Yixuan Tang, Hwee Tou Ng, and Anthony Tung · 2021
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Answering complex open-domain questions with multi-hop dense retrieval
Wenhan Xiong, Xiang Li, Srini Iyer, Jingfei Du, Patrick Lewis, William Yang Wang, Yashar Mehdad, Scott Yih, Sebastian Riedel, Douwe Kiela, and Barlas Oguz · 2021
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Ar-lsat: Investigating analytical reasoning of text
Wanjun Zhong, Siyuan Wang, Duyu Tang, Zenan Xu, Daya Guo, Jiahai Wang, Jian Yin, Ming Zhou, and Nan Duan · 2021
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Entailment tree explanations via iterative retrieval-generation reasoner
Danilo Neves Ribeiro, Shen Wang, Xiaofei Ma, Rui Dong, Xiaokai Wei, Henghui Zhu, Xinchi Chen, Peng Xu, Zhiheng Huang, Andrew Arnold, and Dan Roth · 2022
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Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, et al · 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
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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
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