Zhaoyang Qu — accepted AI-conference papers

2026

Failure Localization in Multi-Agent Code Generation via Knowledge-Guided and Transferable Reasoning

Mingyang Geng, Shanzhi Gu, Zhipeng Liu, Chuanfu Xu, Zhaoyang Qu, Haotian Wang

AAAI 2026technical

Recent advances in multi-agent Large Language Model-based code generation enable collaborative software development through role-specialized agents. However, failure localization of code generation remains challenging due to inter-agent dependencies and solution-path multiplicity. Consequently, exis

Cited by 0 Source ↗PDF ↗Scholar ↗

2026

Mitigating Collaboration Degeneration in Multi-Agent Code Generation via a Controllable Competitive Collaboration Approach

Shanzhi Gu, Mingyang Geng, Yihong Dong, Yunxin Mao, Zhaoyang Qu, Hao Zou +4

IJCAI 2026

Empowered by large language models (LLMs), multi-agent systems (MAS) have shown significant potential in code generation by simulating collaborative workflows. However, we identify a collaboration degeneration phenomenon, where one agent dominates while others remain disengaged, occurring in 38.4% o

Cited by 0 Scholar ↗