AI RESEARCH
AgentDisCo: Towards Disentanglement and Collaboration in Open-ended Deep Research Agents
arXiv CS.CL
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ArXi:2605.11732v1 Announce Type: cross In this paper, we present AgentDisCo, a novel Disentangled and Collaborative agentic architecture that formulates deep research as an adversarial optimization problem between information exploration and exploitation. Unlike existing approaches that conflate these two processes into a single module, AgentDisCo employs a critic agent to evaluate generated outlines and refine search queries, and a generator agent to retrieve updated results and revise outlines accordingly.