1 citations · 1 across the 5 of their papers we have counts for
5 papers
PLawBench: A Rubric-Based Benchmark for Evaluating LLMs in Real-World Legal Practice
Yuzhen Shi, Huanghai Liu, Yiran Hu +27
As large language models (LLMs) are increasingly applied to legal domain-specific tasks, evaluating their ability to perform legal work in real-world settings has become essential.…
Evaluation of Large Language Models in Legal Applications: Challenges, Methods, and Future Directions
Yiran Hu, Huanghai Liu, Chong Wang +15
Large language models (LLMs) are being increasingly integrated into legal applications, including judicial decision support, legal practice assistance, and public-facing legal serv…
J&H: Evaluating the Robustness of Large Language Models Under Knowledge-Injection Attacks in Legal Domain
Yiran Hu, Huanghai Liu, Qingjing Chen +5
As the scale and capabilities of Large Language Models (LLMs) increase, their applications in knowledge-intensive fields such as legal domain have garnered widespread attention. Ho…
JUREX-4E: Juridical Expert-Annotated Four-Element Knowledge Base for Legal Reasoning
Huanghai Liu, Quzhe Huang, Qingjing Chen +5
In recent years, Large Language Models (LLMs) have been widely applied to legal tasks. To enhance their understanding of legal texts and improve reasoning accuracy, a promising app…
LEEC: A Legal Element Extraction Dataset with an Extensive Domain-Specific Label System
Xue Zongyue, Liu Huanghai, Hu Yiran +4
As a pivotal task in natural language processing, element extraction has gained significance in the legal domain. Extracting legal elements from judicial documents helps enhance in…