collaborators

18 papers

cs.SE2026

Turning Interaction History into Execution State: A Runtime Layer for Long-Horizon Coding Agents

Zehao Wang, Yisen Xu, Chenglin Li +5

Long-horizon coding agents accumulate hundreds of actions and observations in their trajectories, yet nothing in this record indicates which observations still describe the reposit…

cs.SE2026

How Do Practitioners Build SE Agents? Insights from a Mixed-Methods Study

Yunbo Lyu, David Williams, Jieke Shi +5

The rise of Software Engineering (SE) agents, i.e., LLM-based agents that can understand large codebases and carry out engineering tasks with limited human intervention, has been m…

cs.SE2026

SetupX: Can LLM Agents Learn from Past Failures in Functionality-Correct Code Repository Setup?

Zihang Zhou, Ziqian Ren, Yukai Wu +7

Functionality-correct repository setup aims to configure execution environments (e.g., dependencies, build scripts) to successfully execute a repository's documented features. It p…

cs.SE2026

Rethinking the Value of Agent-Generated Tests for LLM-Based Software Engineering Agents

Zhi Chen, Zhensu Sun, Yuling Shi +4

Large Language Model (LLM) code agents increasingly resolve repository-level issues by iteratively editing code, invoking tools, and validating candidate patches. In these workflow…

cs.SE2026

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…

cs.AI2026

Yunjue Agent Tech Report: A Fully Reproducible, Zero-Start In-Situ Self-Evolving Agent System for Open-Ended Tasks

Haotian Li, Shijun Yang, Weizhen Qi +5

Conventional agent systems often struggle in open-ended environments where task distributions continuously drift and external supervision is scarce. Their reliance on static toolse…