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Towards Supporting Legal Argumentation with NLP: Is More Data Really All You Need?

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arxiv 2406.10974 v3 pith:7J5EYZMX submitted 2024-06-16 cs.CL cs.AI

classification cs.CLcs.AI
keywords legalapproachesargumentationsymbolicadvancesalwaysappropriatebalance
verification ladder T0 review T1 audit T2 compute T3 formal
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Modeling legal reasoning and argumentation justifying decisions in cases has always been central to AI & Law, yet contemporary developments in legal NLP have increasingly focused on statistically classifying legal conclusions from text. While conceptually simpler, these approaches often fall short in providing usable justifications connecting to appropriate legal concepts. This paper reviews both traditional symbolic works in AI & Law and recent advances in legal NLP, and distills possibilities of integrating expert-informed knowledge to strike a balance between scalability and explanation in symbolic vs. data-driven approaches. We identify open challenges and discuss the potential of modern NLP models and methods that integrate

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Cited by 1 Pith paper

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  1. LLMs for Legal Subsumption in German Employment Contracts

    cs.CL 2025-07 conditional novelty 5.0 of 10

    LLMs reach 80% weighted F1 on German employment contract clause review when given lawyer-distilled examination guidelines, but lag human lawyers when reading full legal sources.

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