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Statutory reasoning is the task of reasoning with facts and statutes, which are rules written in natural language by a legislature.
A logic for statutes
Sarah B Lawsky. 2017 · 2017
Earlier work this paper cites.
A Call for Clarity in Reporting BLEU Scores. In Proceedings of the Third Conference on Machine Translation: Research Papers . Association for Computational Linguistics, Belgium, Brussels, 186–191
Matt Post. 2018 · 2018
Earlier work this paper cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) . Association for Computational Linguistics, Minneapolis, Minnesota, 4171–4186
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Earlier work this paper cites.
Language Models are Few-Shot Learners. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual , Hugo Larochelle, Marc’Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, and Hsuan-Tien Lin (Eds.)
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared 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 M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher 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 · 2020
Earlier work this paper cites.
A Dataset for Statutory Reasoning in Tax Law Entailment and Question Answering. In Proceedings of the Natural Legal Language Processing Workshop 2020 co-located with the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2020), Virtual Workshop, August 24, 2020 (CEUR Workshop Proceedings, Vol. 2645) , Nikolaos Aletras, Ion Androutsopoulos, Leslie Barrett, Adam Meyers, and Daniel Preotiuc-Pietro (Eds.). CEUR-WS.org, 31–38
Nils Holzenberger, Andrew Blair-Stanek, and Benjamin Van Durme. 2020 · 2020
Earlier work this paper cites.
The Gap between Deep Learning and Law: Predicting Employment Notice. In Proceedings of the Natural Legal Language Processing Workshop 2020 co-located with the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2020), Virtual Workshop, August 24, 2020 (CEUR Workshop Proceedings, Vol. 2645) , Nikolaos Aletras, Ion Androutsopoulos, Leslie Barrett, Adam Meyers, and Daniel Preotiuc-Pietro (Eds.). CEUR-WS.org, 52–56
Jason T. Lam, David Liang, Samuel Dahan, and Farhana H. Zulkernine. 2020 · 2020
Earlier work this paper cites.
Iteratively Questioning and Answering for Interpretable Legal Judgment Prediction. In The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020 . AAAI Press, 1250–1257
Haoxi Zhong, Yuzhong Wang, Cunchao Tu, Tianyang Zhang, Zhiyuan Liu, and Maosong Sun. 2020 · 2020
Earlier work this paper cites.
Measuring Massive Multitask Language Understanding. In 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021 . OpenReview.net
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2021 · 2021
Earlier work this paper cites.
Factoring Statutory Reasoning as Language Understanding Challenges. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL/IJCNLP 2021, (Volume 1: Long Papers), Virtual Event, August 1-6, 2021 , Chengqing Zong, Fei Xia, Wenjie Li, and Roberto Navigli (Eds.). Association for Computational Linguistics, 2742–2758
Nils Holzenberger and Benjamin Van Durme. 2021 · 2021
Earlier work this paper cites.
Discovering Explanatory Sentences in Legal Case Decisions Using Pre-trained Language Models. In Findings of the Association for Computational Linguistics: EMNLP 2021 . 4273–4283
Jaromír Šavelka and Kevin D Ashley. 2021a · 2021
Cited alongside, same era.
Legal information retrieval for understanding statutory terms
Jaromír Šavelka and Kevin D Ashley. 2021b · 2021
Cited alongside, same era.
GPT-J-6B: A 6 Billion Parameter Autoregressive Language Model
Ben Wang and Aran Komatsuzaki. 2021 · 2021
Cited alongside, same era.
Judicial knowledge-enhanced magnitude-aware reasoning for numerical legal judgment prediction
Sheng Bi, Zhiyao Zhou, Lu Pan, and Guilin Qi. 2022 · 2022
Cited alongside, same era.
Michael Bommarito, II and Daniel Martin Katz. 2022 · 2022
Cited alongside, same era.
Overview and Discussion of the Competition on Legal Information Extraction/Entailment (COLIEE) 2021
Juliano Rabelo, Randy Goebel, Mi-Young Kim, Yoshinobu Kano, Masaharu Yoshioka, and Ken Satoh. 2022 · 2022
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Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought
Abulhair Saparov and He He. 2022 · 2022
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Optimizing Language Models for Argumentative Reasoning. In Proceedings of the 1st Workshop on Argumentation & Machine Learning co-located with 9th International Conference on Computational Models of Argument (COMMA 2022), Cardiff, Wales, September 13th, 2022 (CEUR Workshop Proceedings, Vol. 3208) , Isabelle Kuhlmann, Jack Mumford, and Stefan Sarkadi (Eds.). CEUR-WS.org, 27–44
Luke Thorburn and Ariel Kruger. 2022 · 2022
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Chain of Thought Prompting Elicits Reasoning in Large Language Models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed H. Chi, Quoc Le, and Denny Zhou. 2022 · 2022
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Thinking about GPT-3 In-Context Learning for Biomedical IE? Think Again. In Findings of the Association for Computational Linguistics: EMNLP 2022, Abu Dhabi, United Arab Emirates, December 7-11, 2022 , Yoav Goldberg, Zornitsa Kozareva, and Yue Zhang (Eds.). Association for Computational Linguistics, 4497–4512
Bernal Jimenez Gutierrez, Nikolas McNeal, Clayton Washington, You Chen, Lang Li, Huan Sun, and Yu Su. 2022 · 2022
Cited alongside, same era.
Decomposed Prompting: A Modular Approach for Solving Complex Tasks
Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson, Peter Clark, and Ashish Sabharwal. 2022 · 2022
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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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Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering
Pan Lu, Swaroop Mishra, Tony Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, and Ashwin Kalyan. 2022 · 2022
Cited alongside, same era.
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Legal Prompting: Teaching a Language Model to Think Like a Lawyer
Fangyi Yu, Lee Quartey, and Frank Schilder. 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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Improved logical reasoning of language models via differentiable symbolic programming. In First Workshop on Pre-training: Perspectives, Pitfalls, and Paths Forward at ICML 2022
Hanlin Zhang, Ziyang Li, Jiani Huang, Mayur Naik, and Eric Xing. 2022 · 2022
Later among the works it cites.
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 H. Chi. 2022 · 2022
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Jonathan H. Choi, Kristin E. Hickman, Amy Monahan, and Daniel B. Schwarcz. 2023 · 2023
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