用可视化工具解析法律论证中的模糊点，帮非专家看懂争议根源。
AF-XRAY: Visual Explanation and Resolution of Ambiguity in Legal Argumentation Frameworks
- 基于博弈论的分层可视化，揭示论证链条的合理性结构。
- 识别关键攻击集，通过暂停特定攻击解决未决论证问题。
- 支持法律解释性推理，展示不同假设如何导致不同结论。
论证框架（AFs）为法律推理提供形式化方法，但对非专家而言，识别模糊来源并解释论证接受性仍具挑战。我们提出 AF-XRAY，一个开源工具包，用于探索、分析和可视化法律推理中的抽象论证框架。该工具引入：(i) 基于博弈论论证长度的分层可视化，揭示合理推导结构；(ii) 按语义角色分类攻击边（主要、次要、错误）；(iii) 在模糊三值稳定语义上叠加多组二值解的可视化；(iv) 识别关键攻击集，其暂停可解决未决论证。通过系统生成关键攻击集，AF-XRAY将模糊场景转化为有根基的解决方案，使用户能定位模糊成因并探索替代化解法。我们以真实法律案例（如 Bench-Capon 模拟的野生动物案）为例，证明该工具支持目的论法律推理，揭示不同假设如何导致不同正当结论。
原文摘要 · Abstract (English)
Argumentation frameworks (AFs) provide formal approaches for legal reasoning, but identifying sources of ambiguity and explaining argument acceptance remains challenging for non-experts. We present AF-XRAY, an open-source toolkit for exploring, analyzing, and visualizing abstract AFs in legal reasoning. AF-XRAY introduces: (i) layered visualizations based on game-theoretic argument length revealing well-founded derivation structures; (ii) classification of attack edges by semantic roles (primary, secondary, blunders); (iii) overlay visualizations of alternative 2-valued solutions on ambiguous 3-valued grounded semantics; and (iv) identification of critical attack sets whose suspension resolves undecided arguments. Through systematic generation of critical attack sets, AF-XRAY transforms ambiguous scenarios into grounded solutions, enabling users to pinpoint specific causes of ambiguity and explore alternative resolutions. We use real-world legal cases (e.g., Wild Animals as modeled by Bench-Capon) to show that our tool supports teleological legal reasoning by revealing how different assumptions lead to different justified conclusions.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。