Beyond Perfect Teammates: Multi-Agent Collaboration with Unreliable Colleagues
LLM-based multi-agent collaboration is increasingly used to solve complex tasks by dividing work among specialized agents and integrating complementary expertise. Yet existing systems and evaluations largely rest on an implicit perfect-colleague assumption: collaborators provide correct and complete information and respond promptly to requests. In realistic teamwork, however, collaborators may return information that does not answer the intended question, provide insufficient detail to support a decision, or fail to respond to a request. To separate task-solving competence from the ability to recover an unreliable evidence-gathering process, we introduce the Unreliable Colleagues Benchmar...
| Authors | Chen Huang, Yiyang Zhang, Yuhao Wu et al. |
|---|---|
| Primary category | cs.AI |
| Published | 12 October 2026 |
| Last updated at source | 14 October 2026 |
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