LLM判案虽技术一致，但社会接受度低，需兼顾任务与各方诉求。
The Consistency-Acceptability Divergence of LLMs in Judicial Decision-Making: Task and Stakeholder Dimensions
- 提出一致性与接受度的分裂问题，揭示技术一致不等于社会认可。
- 基于2023–2025年数据发现，单一技术优化无法解决社会信任缺口。
- 设计双轨协同框架，支持多角色互动与智能任务分类，适合政策制定者参考。
大语言模型（LLM）正全球重塑司法实践，但其技术一致性与社会接受度之间存在显著矛盾。本研究首次提出“一致性-接受度分裂”概念，指技术层面高度一致却引发社会争议的现象。通过对2023–2025年最新司法领域LLM应用数据的综合分析，发现该问题需从任务维度与利益相关方维度共同应对。为此，本文提出双轨审议多角色LLM司法治理框架（DTDMR-LJGF），实现智能任务分类与多元主体间有意义互动。该框架兼具理论深度与实践价值，为构建兼顾技术效率与社会合法性的LLM司法生态提供路径。
原文摘要 · Abstract (English)
The integration of large language model (LLM) technology into judicial systems is fundamentally transforming legal practice worldwide. However, this global transformation has revealed an urgent paradox requiring immediate attention. This study introduces the concept of ``consistency-acceptability divergence'' for the first time, referring to the gap between technical consistency and social acceptance. While LLMs achieve high consistency at the technical level, this consistency demonstrates both positive and negative effects. Through comprehensive analysis of recent data on LLM judicial applications from 2023--2025, this study finds that addressing this challenge requires understanding both task and stakeholder dimensions. This study proposes the Dual-Track Deliberative Multi-Role LLM Judicial Governance Framework (DTDMR-LJGF), which enables intelligent task classification and meaningful interaction among diverse stakeholders. This framework offers both theoretical insights and practical guidance for building an LLM judicial ecosystem that balances technical efficiency with social legitimacy.
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