1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.AI2025
EvolMathEval: Towards Evolvable Benchmarks for Mathematical Reasoning via Evolutionary Testing
Shengbo Wang, Mingwei Liu, Zike Li +4
The rapid advancement of Large Language Models (LLMs) poses a significant challenge to existing mathematical reasoning benchmarks. However, these benchmarks tend to become easier o…
cs.SE2025
Code Copycat Conundrum: Demystifying Repetition in LLM-based Code Generation
Mingwei Liu, Juntao Li, Ying Wang +9
Despite recent advances in Large Language Models (LLMs) for code generation, the quality of LLM-generated code still faces significant challenges. One significant issue is code rep…
cs.SE2025★ 1 cited
RustEvo^2: An Evolving Benchmark for API Evolution in LLM-based Rust Code Generation
Linxi Liang, Jing Gong, Mingwei Liu +5
Large Language Models (LLMs) have become pivotal tools for automating code generation in software development. However, these models face significant challenges in producing versio…