most citedOOP: Object-Oriented Programming Evaluation Benchmark for Large Language Models

3 citations · 3 across the 5 of their papers we have counts for

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cs.SE2025

A Multi-Language Object-Oriented Programming Benchmark for Large Language Models

Shuai Wang, Liang Ding, Li Shen +4

Establishing fair and robust benchmarks is essential for evaluating intelligent code generation by large language models (LLMs). Our survey of 35 existing benchmarks uncovers three…

cs.SE2025

Leveraging Metamemory Agent for Enhanced Data-Free Code Generation in Large Language Models

Shengsheng Zhou, Shuai Wang, Liang Ding +5

Large language models (LLMs) have shown strong performance in automated code generation, with few-shot prompting widely used for its simplicity and effectiveness. However, few-shot…

cs.SE2024

: Improving Code Generation of LLMs by Uncertainty-Aware Selective Contrastive Decoding

Shuai Wang, Liang Ding, Li Shen +4

Large language models (LLMs) have shown remarkable capabilities in code generation. However, the effects of hallucinations (e.g., output noise) make it particularly challenging for…