13 citations · 20 across the 23 of their papers we have counts for
12 papers · 1 filter
AdaGReS:Adaptive Greedy Context Selection via Redundancy-Aware Scoring for Token-Budgeted RAG
Chao Peng, Bin Wang, Zhilei Long +1
Retrieval-augmented generation (RAG) is highly sensitive to the quality of selected context, yet standard top-k retrieval often returns redundant or near-duplicate chunks that wast…
GraphLocator: Graph-guided Causal Reasoning for Issue Localization
Wei Liu, Chao Peng, Pengfei Gao +4
The issue localization task aims to identify the locations in a software repository that requires modification given a natural language issue description. This task is fundamental…
More with Less: An Empirical Study of Turn-Control Strategies for Efficient Coding Agents
Pengfei Gao, Chao Peng
LLM-powered coding agents, which operate in iterative loops (turns) to solve software engineering tasks, are becoming increasingly powerful. However, their practical deployment is…
Scalable Supervision for Software Agents via Patch Reasoning
Junjielong Xu, Boyin Tan, Xiaoyuan Liu +3
While language model agents have advanced software engineering, existing test-based supervision is limiting its scalability on real-world issues. The reason is twofold: (1) high-co…
Extending Fill-In-the-Middle with Instructions for Steerable Code Completion
Zhensu Sun, Chengran Yang, Chao Peng +4
Code completion models often fail when the developer's intent is under-specified in the code context. To mitigate this, developers frequently use natural language comments to clari…
Reducing Cost of LLM Agents with Trajectory Reduction
Yuan-An Xiao, Pengfei Gao, Chao Peng +1
Multi-turn agent systems based on Large Language Models (LLMs) have become increasingly popular for software engineering tasks. While LLM agents demonstrate promising effectiveness…
Tool-integrated Reinforcement Learning for Repo Deep Search
Zexiong Ma, Chao Peng, Qunhong Zeng +3
Issue localization, the process of identifying code locations that need modification to resolve software issues, is a critical yet challenging task in software development. The sem…
Trae Agent: An LLM-based Agent for Software Engineering with Test-time Scaling
Trae Research Team, Pengfei Gao, Zhao Tian +12
Software issue resolution is a critical challenge in software engineering and has garnered increasing attention in recent years. With the rapid advancement of large language models…
SafeGenBench: A Benchmark Framework for Security Vulnerability Detection in LLM-Generated Code
Xinghang Li, Jingzhe Ding, Chao Peng +4
The code generation capabilities of large language models(LLMs) have emerged as a critical dimension in evaluating their overall performance. However, prior research has largely ov…
CodeVisionary: An Agent-based Framework for Evaluating Large Language Models in Code Generation
Xinchen Wang, Pengfei Gao, Chao Peng +2
Large language models (LLMs) have demonstrated strong capabilities in code generation, underscoring the critical need for rigorous and comprehensive evaluation. Existing evaluation…
SoRFT: Issue Resolving with Subtask-oriented Reinforced Fine-Tuning
Zexiong Ma, Chao Peng, Pengfei Gao +3
Mainstream issue-resolving frameworks predominantly rely on commercial models, leading to high costs and privacy concerns. Existing training approaches for issue resolving struggle…
Repo2Run: Automated Building Executable Environment for Code Repository at Scale
Ruida Hu, Chao Peng, Xinchen Wang +2
Scaling up executable code data is significant for improving language models' software engineering capability. The intricate nature of the process makes it labor-intensive, time-co…