activity
20232025
most citedLawBench: Benchmarking Legal Knowledge of Large Language Models

21 citations · 23 across the 6 of their papers we have counts for

collaborators
Showing cs.CLShow all

7 papers · 1 filter

cs.CL2025

MultiJustice: A Chinese Dataset for Multi-Party, Multi-Charge Legal Prediction

Xiao Wang, Jiahuan Pei, Diancheng Shui +4

Legal judgment prediction offers a compelling method to aid legal practitioners and researchers. However, the research question remains relatively under-explored: Should multiple d…

cs.CL2024

The Accuracy Paradox in RLHF: When Better Reward Models Don't Yield Better Language Models

Yanjun Chen, Dawei Zhu, Yirong Sun +3

Reinforcement Learning from Human Feedback significantly enhances Natural Language Processing by aligning language models with human expectations. A critical factor in this alignme…

cs.CL2024

To Preserve or To Compress: An In-Depth Study of Connector Selection in Multimodal Large Language Models

Junyan Lin, Haoran Chen, Dawei Zhu +1

In recent years, multimodal large language models (MLLMs) have garnered significant attention from both industry and academia. However, there is still considerable debate on constr…

cs.CL2024

From Calculation to Adjudication: Examining LLM judges on Mathematical Reasoning Tasks

Andreas Stephan, Dawei Zhu, Matthias Aßenmacher +2

To reduce the need for human annotations, large language models (LLMs) have been proposed as judges of the quality of other candidate models. The performance of LLM judges is typic…

cs.CL2024

Assessing "Implicit" Retrieval Robustness of Large Language Models

Xiaoyu Shen, Rexhina Blloshmi, Dawei Zhu +2

Retrieval-augmented generation has gained popularity as a framework to enhance large language models with external knowledge. However, its effectiveness hinges on the retrieval rob…

cs.CL20242 cited

InternLM-Law: An Open Source Chinese Legal Large Language Model

Zhiwei Fei, Songyang Zhang, Xiaoyu Shen +9

While large language models (LLMs) have showcased impressive capabilities, they struggle with addressing legal queries due to the intricate complexities and specialized expertise r…