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Large Language Models (LLMs) could struggle to fully understand legal theories and perform complex legal reasoning tasks.
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, et al. 2020 · 1901
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Rhetoric and the rule of law: a theory of legal reasoning
Neil MacCormick. 2005 · 2005
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Experiential learning: Experience as the source of learning and development
David A Kolb. 2014 · 2014
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Cail2018: A large-scale legal dataset for judgment prediction
Chaojun Xiao, Haoxi Zhong, Zhipeng Guo, Cunchao Tu, Zhiyuan Liu, Maosong Sun, Yansong Feng, Xianpei Han, Zhen Hu, Heng Wang, et al. 2018 · 2018
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Legal judgment prediction via topological learning
Haoxi Zhong, Zhipeng Guo, Cunchao Tu, Chaojun Xiao, Zhiyuan Liu, and Maosong Sun. 2018 · 2018
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Neural legal judgment prediction in English
Ilias Chalkidis, Ion Androutsopoulos, and Nikolaos Aletras. 2019 · 2019
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Legal intelligence: Algorithmic, data, and social challenges
Changlong Sun, Yating Zhang, Xiaozhong Liu, and Fei Wu. 2020 · 2020
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Augmented SBERT: Data augmentation method for improving bi-encoders for pairwise sentence scoring tasks
Nandan Thakur, Nils Reimers, Johannes Daxenberger, and Iryna Gurevych. 2021 · 2021
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Lawformer: A pre-trained language model for chinese legal long documents
Chaojun Xiao, Xueyu Hu, Zhiyuan Liu, Cunchao Tu, and Maosong Sun. 2021 · 2021
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Neurjudge: A circumstance-aware neural framework for legal judgment prediction
Linan Yue, Qi Liu, Binbin Jin, Han Wu, Kai Zhang, Yanqing An, Mingyue Cheng, Biao Yin, and Dayong Wu. 2021 · 2021
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Do charge prediction models learn legal theory?
Zhenwei An, Quzhe Huang, Cong Jiang, Yansong Feng, and Dongyan Zhao. 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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Augmenting legal judgment prediction with contrastive case relations
Dugang Liu, Weihao Du, Lei Li, Weike Pan, and Zhong Ming. 2022 · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al. 2022 · 2022
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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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How ready are pre-trained abstractive models and llms for legal case judgement summarization?
Aniket Deroy, Kripabandhu Ghosh, and Saptarshi Ghosh. 2023 · 2023
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Towards reasoning in large language models: A survey
Jie Huang and Kevin Chen-Chuan Chang. 2023 · 2023
Large legal fictions: Profiling legal hallucinations in large language models
Matthew Dahl, Varun Magesh, Mirac Suzgun, and Daniel E Ho. 2024 · 2024
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Legalbench: A collaboratively built benchmark for measuring legal reasoning in large language models
Neel Guha, Julian Nyarko, Daniel Ho, Christopher Ré, Adam Chilton, Alex Chohlas-Wood, Austin Peters, Brandon Waldon, Daniel Rockmore, Diego Zambrano, et al. 2024 · 2024
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Simucourt: Building judicial decision-making agents with real-world judgement documents
Zhitao He, Pengfei Cao, Chenhao Wang, Zhuoran Jin, Yubo Chen, Jiexin Xu, Huaijun Li, Xiaojian Jiang, Kang Liu, and Jun Zhao. 2024 · 2024
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From graph to word bag: Introducing domain knowledge to confusing charge prediction
Ang Li, Qiangchao Chen, Yiquan Wu, Xiang Zhou, Kun Kuang, Fei Wu, and Ming Cai. 2024 · 2024
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Interpretable long-form legal question answering with retrieval-augmented large language models
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Natural language processing in the legal domain
Daniel Martin Katz, Dirk Hartung, Lauritz Gerlach, Abhik Jana, and Michael J Bommarito II. 2023 · 2023
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Multilegalpile: A 689gb multilingual legal corpus
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Large language models can be easily distracted by irrelevant context
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Llama: Open and efficient foundation language models
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