most citedLawBench: Benchmarking Legal Knowledge of Large Language Models

21 citations · 28 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024★ 1 cited

CIBench: Evaluating Your LLMs with a Code Interpreter Plugin

Chuyu Zhang, Songyang Zhang, Yingfan Hu +8

While LLM-Based agents, which use external tools to solve complex problems, have made significant progress, benchmarking their ability is challenging, thereby hindering a clear und…

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.CL2024★ 3 cited

InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning

Huaiyuan Ying, Shuo Zhang, Linyang Li +19

The math abilities of large language models can represent their abstract reasoning ability. In this paper, we introduce and open-source our math reasoning LLMs InternLM-Math which…

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…