3 citations · 7 across the 22 of their papers we have counts for
10 papers · 1 filter
Benchmarking LLMs for Fine-Grained Code Review with Enriched Context in Practice
Ruida Hu, Xinchen Wang, Xin-Cheng Wen +5
Code review is a cornerstone of software quality assurance, and recent advances in Large Language Models (LLMs) have shown promise in its automation. However, existing benchmarks f…
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…
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…
CoReQA: Uncovering Potentials of Language Models in Code Repository Question Answering
Jialiang Chen, Kaifa Zhao, Jie Liu +6
Large language models that enhance software development tasks, such as code generation, code completion, and code question answering (QA), have been extensively studied in both aca…