ViLegalNLI：越南法律文本的自然语言推理
ViLegalNLI: Natural Language Inference for Vietnamese Legal Texts
AI总结：
本文提出ViLegalNLI，首个针对法律领域构建的越南语自然语言推理数据集，包含42,012个前提-假设对，涵盖多种法律领域，用于评估法律推理的结构逻辑与术语一致性。
摘要：
本文介绍ViLegalNLI，首个大规模越南语自然语言推理（NLI）数据集，专门针对法律领域构建。该数据集包含42,012个前提-假设对，源自官方法规文件，并标注了二元推理标签（蕴含和不蕴含）。它覆盖多个法律领域，反映了现实法律推理场景，具有结构化逻辑、条件句和领域特定术语。为构建ViLegalNLI，我们提出了一种半自动数据生成框架，整合大语言模型进行受控假设生成和系统化质量验证流程。该框架包含消除伪影策略和跨模型验证，以提高标注可靠性并确保法律一致性。生成的数据集捕捉了多样化的推理模式，包括改写、逻辑推论和法律无效推论，从而为越南语法律推理任务提供全面的基准。我们对ViLegalNLI进行了广泛实验，使用多语言模型、越南语专用预训练语言模型和指令调优的大语言模型。结果表明，少样本LLM配置始终能取得优越性能，而性能显著受假设长度、词汇重叠和推理复杂性影响。跨领域评估进一步揭示了在不同法律领域泛化法律推理的挑战。总体而言，ViLegalNLI为越南语法律NLI建立了基础基准，并支持未来法律推理、法规文本理解及可靠AI系统在法律分析和决策支持中的发展。该数据集可供研究使用。
英文摘要：
In this article, we introduce ViLegalNLI, the first large-scale Vietnamese Natural Language Inference (NLI) dataset specifically constructed for the legal domain. The dataset consists of 42,012 premise-hypothesis pairs derived from official statutory documents and annotated with binary inference labels (Entailment and Non-entailment). It covers multiple legal domains and reflects realistic legal reasoning scenarios characterized by structured logic, conditional clauses, and domain-specific terminology. To construct ViLegalNLI, we propose a semi-automatic data generation framework that integrates large language models for controlled hypothesis generation and systematic quality validation procedures. The framework incorporates artifact mitigation strategies and cross-model validation to improve annotation reliability and ensure legal consistency. The resulting dataset captures diverse reasoning patterns, including paraphrasing, logical implication, and legally invalid inferences, thereby providing a comprehensive benchmark for Vietnamese legal inference tasks. We conduct extensive experiments on the ViLegalNLI using multilingual models, Vietnamese-specific pretrained language models, and instruction-tuned large language models. The results show that few-shot LLM configurations consistently achieve superior performance, while performance is significantly influenced by hypothesis length, lexical overlap, and reasoning complexity. Cross-domain evaluations further reveal the challenges of generalizing legal inference across distinct legal fields. Overall, ViLegalNLI establishes a foundational benchmark for Vietnamese legal NLI and supports future research in legal reasoning, statutory text understanding, and the development of reliable AI systems for legal analysis and decision support. The dataset is publicly available for research purposes.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
