activity
20232026
most citedA Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

23 citations · 76 across the 61 of their papers we have counts for

collaborators

63 papers

cs.SE2026

Efficient SWE Agent Benchmarking via Trajectory-Aware Evaluation

Kefeng Duan, Dewu Zheng, Yanlin Wang +7

Evaluating software engineering agents on realistic benchmarks is costly, since each task may require multi-step code exploration, modification, and test execution. Existing effici…

cs.SE2026

Adaptive Critical Token-Aware Retrieval for Repository-Level Code Generation

Kefeng Duan, Dewu Zheng, Yanlin Wang +8

The repository-level code generation task requires synthesizing code that satisfies task requirements while remaining consistent with the target repository context. Since real-worl…

cs.SE2026

SWE-Prime: Fewer Trajectories, Better Performance

Dewu Zheng, Ruizhe Ye, Yanlin Wang +7

To improve large language models' ability to resolve real-world software issues, prior work has focused on constructing large-scale agent trajectory datasets and performing supervi…

cs.SE2026

From Static to Dynamic: Benchmarking Real-World Code Review with MCR-Bench

Dewu Zheng, Yanlin Wang, Xiwen Wang +5

In real-world software development, code review typically involves iterative interactions between developers and reviewers to improve software quality, making the process costly an…

cs.SE2026

RepoReasoner: Evaluating Repository-Level Code Reasoning Ability of Long-Context Language Models

Yanlin Wang, Suiquan Wang, Yanli Wang +4

Recent large language models (LLMs) have shown strong performance on software engineering tasks, yet most existing benchmarks evaluate code reasoning at the function level, where a…

cs.SE2026

VRExplorer: A Model-based Approach for Semi-Automated Testing of Virtual Reality Scenes

Zhengyang Zhu, Hong-Ning Dai, Hanyang Guo +2

With the proliferation of Virtual Reality (VR) markets, VR applications are rapidly expanding in scale and complexity, thereby driving an urgent need for assuring VR software quali…