@inproceedings{liu-etal-2026-lexgenius,
    title = "{L}ex{G}enius: An Expert-Level Benchmark for Large Language Models in Legal General Intelligence",
    author = "Liu, Wenjin  and
      Luo, Haoran  and
      Feng, Xin  and
      Ji, Xiang  and
      Zhou, Lijuan  and
      Mao, Rui  and
      Wang, Jiapu  and
      Pan, Shirui  and
      Cambria, Erik",
    editor = "Liakata, Maria  and
      Moreira, Viviane P.  and
      Zhang, Jiajun  and
      Jurgens, David",
    booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {ACL} 2026",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl/2026.findings-acl.926/",
    pages = "18565--18585",
    ISBN = "979-8-89176-395-1",
    abstract = "Legal general intelligence (GI) refers to artificial intelligence (AI) that encompasses legal understanding, reasoning, and decision-making, simulating the expertise of legal experts across domains. However, existing benchmarks are result-oriented and fail to systematically evaluate the legal intelligence of large language models (LLMs), hindering the development of legal GI. To address this, we propose LexGenius, an expert-level Chinese legal benchmark for evaluating legal GI in LLMs. It follows a Dimension-Task-Ability framework, covering seven dimensions, eleven tasks, and twenty abilities. We use the recent legal cases and exam questions to create multiple-choice questions with a combination of manual and LLM reviews to reduce data leakage risks, ensuring accuracy and reliability through multiple rounds of checks. We evaluate 12 state-of-the-art LLMs using LexGenius and conduct an in-depth analysis. We find significant disparities across legal intelligence abilities for LLMs, with even the best LLMs lagging behind human legal professionals. We believe LexGenius can assess the legal intelligence abilities of LLMs and enhance legal GI development.Our project is available at https://github.com/QwenQKing/LexGenius."
}