AgentDisCo: Towards Disentanglement and Collaboration in Open-ended Deep Research Agents
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. The iteratively refined outline is then passed to a downstream report writer that synthesizes a comprehensive research report. The overall workflow supports both handcrafted and automatically discovered design strategies v...
| Authors | Jiarui Jin, Zexuan Yan, Shijian Wang et al. |
|---|---|
| Primary category | cs.IR |
| Published | 12 May 2026 |
| Last updated at source | 4 June 2026 |
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