mlsanityData to 7 Oct 2026

Evaluation Ethics of LLMs in Legal Domain

arXiv 2403.11152 ↗First posted 17 Mar 2024cs.CL cs.AIcited by 8

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Abstract (arXiv)

In recent years, the utilization of large language models for natural language dialogue has gained momentum, leading to their widespread adoption across various domains. However, their universal competence in addressing challenges specific to specialized fields such as law remains a subject of scrutiny. The incorporation of legal ethics into the model has been overlooked by researchers. We asserts that rigorous ethic evaluation is essential to ensure the effective integration of large language models in legal domains, emphasizing the need to assess domain-specific proficiency and domain-specific ethic. To address this, we propose a novelty evaluation methodology, utilizing authentic legal cases to evaluate the fundamental language abilities, specialized legal knowledge and legal robustness of large language models (LLMs). The findings from our comprehensive evaluation contribute significantly to the academic discourse surrounding the suitability and performance of large language models in legal domains.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 4 of its 18 references that are in the map. First posted on arXiv 17 Mar 2024.

Builds on

4 of 18 references.

References · 4

  1. 2023AGIEval: A Human-Centric Benchmark for Evaluating Foundation Modelscited by 701
  2. 2023Baichuan 2: Open Large-scale Language Modelscited by 664
  3. 2023A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethicscited by 162
  4. 2023Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts Architecturecited by 119

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 3; 2026: 3.

8 papers.