Zhexu Wang — accepted AI-conference papers

2025

CS-Bench: A Comprehensive Benchmark for Large Language Models towards Computer Science Mastery

Xiaoshuai Song, Muxi Diao, Guanting Dong, Zhengyang Wang, Yujia Fu, Runqi Qiao +10

ICLR 2025poster

Large language models (LLMs) have demonstrated significant potential in advancing various fields of research and society. However, the current community of LLMs overly focuses on benchmarks for analyzing specific foundational skills (e.g. mathematics and code generation), neglecting an all-round eva…

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2024

How Do Your Code LLMs perform? Empowering Code Instruction Tuning with Really Good Data

Yejie Wang, Keqing He, Dayuan Fu, Zhuoma GongQue, Heyang Xu, Yanxu Chen +8

EMNLP 2024main

Recently, there has been a growing interest in studying how to construct better code instruction tuning data. However, we observe Code models trained with these datasets exhibit high performance on HumanEval but perform worse on other benchmarks such as LiveCodeBench. Upon further investigation, we…

Cited by 3 Source ↗PDF ↗code ↗Scholar ↗