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20242026
most citedPractically implementing an LLM-supported collaborative vulnerability remediation process: a team-based approach

9 citations · 9 across the 3 of their papers we have counts for

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cs.AI2026

Finding Where the Buck Stops: An Automated Failure Attribution-Based Reflection Framework for Multi-Agent Collaboration

Xiaoqing Wang, Keman Huang, Bin Liang +3

Multi-agent systems (MAS) powered by large language models have shown promise for complex tasks but suffer from high failure rates. Current self-reflection methods for MAS require…