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

21 citations · 25 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SE2025★ 1 cited

From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligence

Jian Yang, Xianglong Liu, Weifeng Lv +68

Large language models (LLMs) have fundamentally transformed automated software development by enabling direct translation of natural language descriptions into functional code, dri…

cs.CL2025

SkipGPT: Dynamic Layer Pruning Reinvented with Token Awareness and Module Decoupling

Anhao Zhao, Fanghua Ye, Yingqi Fan +4

Large language models (LLMs) achieve remarkable performance across tasks but incur substantial computational costs due to their deep, multi-layered architectures. Layer pruning has…

cs.CL2024★ 2 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…

cs.CL2024★ 1 cited

MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics Benchmark

Hongwei Liu, Zilong Zheng, Yuxuan Qiao +7

Recent advancements in large language models (LLMs) have showcased significant improvements in mathematics. However, traditional math benchmarks like GSM8k offer a unidimensional p…

cs.CL2023★ 21 cited

LawBench: Benchmarking Legal Knowledge of Large Language Models

Zhiwei Fei, Xiaoyu Shen, Dawei Zhu +6

Large language models (LLMs) have demonstrated strong capabilities in various aspects. However, when applying them to the highly specialized, safe-critical legal domain, it is uncl…