1 citations · 1 across the 7 of their papers we have counts for
9 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…
JustEva: A Toolkit to Evaluate LLM Fairness in Legal Knowledge Inference
Zongyue Xue, Siyuan Zheng, Shaochun Wang +8
The integration of Large Language Models (LLMs) into legal practice raises pressing concerns about judicial fairness, particularly due to the nature of their "black-box" processes.…
LLMs on Trial: Evaluating Judicial Fairness for Large Language Models
Yiran Hu, Zongyue Xue, Haitao Li +10
Large Language Models (LLMs) are increasingly used in high-stakes fields where their decisions impact rights and equity. However, LLMs' judicial fairness and implications for socia…
JuDGE: Benchmarking Judgment Document Generation for Chinese Legal System
Weihang Su, Baoqing Yue, Qingyao Ai +6
This paper introduces JuDGE (Judgment Document Generation Evaluation), a novel benchmark for evaluating the performance of judgment document generation in the Chinese legal system.…
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…