collaborators

5 papers

cs.AI2026

Learning Adaptive Parallel Execution for Efficient Code Localization

Ke Xu, Siyang Xiao, Ming Liang +6

Code localization constitutes a key bottleneck in automated software development pipelines. While concurrent tool execution can enhance discovery speed, current agents demonstrate…

cs.CL2026

Rethinking Memory as Continuously Evolving Connectivity

Jizhan Fang, Buqiang Xu, Zhixian Wang +12

Existing memory-augmented LLM agents often treat memory as a static repository with pre-defined representations and fixed retrieval pipelines, which is brittle in dynamic agentic e…

cs.SE2026

One Tool Is Enough: Reinforcement Learning for Repository-Level LLM Agents

Zhaoxi Zhang, Yitong Duan, Yanzhi Zhang +9

Locating files and functions requiring modification in large software repositories is challenging due to their scale and structural complexity. Existing LLM-based methods typically…

cs.AI2026

Securing the Floor and Raising the Ceiling: A Merging-based Paradigm for Multi-modal Search Agents

Zhixiang Wang, Jingxuan Xu, Dajun Chen +3

Recent advances in Vision-Language Models (VLMs) have motivated the development of multi-modal search agents that can actively invoke external search tools and integrate retrieved…

cs.SE2026

EGSS: Entropy-guided Stepwise Scaling for Reliable Software Engineering

Chenhui Mao, Yuanting Lei, Zhixiang Wei +6

Agentic Test-Time Scaling (TTS) has delivered state-of-the-art (SOTA) performance on complex software engineering tasks such as code generation and bug fixing. However, its practic…