ClaimGen-CN: A Large-scale Chinese Dataset for Legal Claim Generation
Legal claims refer to the plaintiff's demands in a case and are essential to
guiding judicial reasoning and case resolution. While many works have focused
on improving the efficiency of legal professionals, the research on helping
non-professionals (e.g., plaintiffs) remains unexplored. This paper explores
the problem of legal claim generation based on the given case's facts. First,
we construct ClaimGen-CN, the first dataset for Chinese legal claim generation
task, from various real-world legal disputes. Additionally, we design an
evaluation metric tailored for assessing the generated claims, which
encompasses two essential dimensions: factuality and clarity. Building on this,
we conduct a comprehensive zero-shot evaluation of state-of-the-art general and
legal-domain large language models. Our findings highlight the limitations of
the current models in factual precision and expressive clarity, pointing to the
need for more targeted development in this domain. To encourage further
exploration of this important task, we will make the dataset publicly
available.
68aefe3d5f5ef03314d8c4bc
Siying Zhou
68aefe3d5f5ef03314d8c4bd
Yiquan Wu
68aefe3d5f5ef03314d8c4be
Hui Chen
68aefe3d5f5ef03314d8c4bf
Xavier Hu
admin_assigned
2025-08-28T19:03:23.630Z
6892b4459f604ad07412f117
/avatars/fb9e54e1689b4add084e32d7e5dd2f16.svg
Xavier Hu
user
xavier-hu
68aefe3d5f5ef03314d8c4c0
Kun Kuang
68aefe3d5f5ef03314d8c4c1
Adam Jatowt
admin_assigned
2025-08-28T19:03:34.354Z
66ad9d0176044810f5d7b912
/avatars/498a3aedfe8e20dd74f2b74ba5e693ea.svg
Adam Jatowt
user
Adammo12
68aefe3d5f5ef03314d8c4c2
Ming Hu
68aefe3d5f5ef03314d8c4c3
Chunyan Zheng
68aefe3d5f5ef03314d8c4c4
Fei Wu
ClaimGen-CN: A Large-scale Chinese Dataset for Legal Claim Generation
Legal claims refer to the plaintiff's demands in a case and are essential to
guiding judicial reasoning and case resolution. While many works have focused
on improving the efficiency of legal professionals, the research on helping
non-professionals (e.g., plaintiffs) remains unexplored. This paper explores
the problem of legal claim generation based on the given case's facts. First,
we construct ClaimGen-CN, the first dataset for Chinese legal claim generation
task, from various real-world legal disputes. Additionally, we design an
evaluation metric tailored for assessing the generated claims, which
encompasses two essential dimensions: factuality and clarity. Building on this,
we conduct a comprehensive zero-shot evaluation of state-of-the-art general and
legal-domain large language models. Our findings highlight the limitations of
the current models in factual precision and expressive clarity, pointing to the
need for more targeted development in this domain. To encourage further
exploration of this important task, we will make the dataset publicly
available.
The paper addresses the generation of legal claims for non-professionals using datasets and evaluation metrics, highlighting the limitations of current models in factual precision and clarity.
ClaimGen-CN legal claim generation zero-shot evaluation large language models factual precision expressive clarity