From Intent to Evidence: A Categorical Approach for Structural Evaluation of Deep Research Agents
Deep Research Agents (DRAs) aim to answer complex questions by searching the web, checking evidence, and synthesizing conclusions across heterogeneous sources. We introduce a category-theoretic framework for evaluating and improving such agents. The framework treats deep research as a structured mapping from user intent to evidence-grounded conclusions, making retrieval traces, cross-source alignment, and final synthesis explicit. Guided by this view, we derive a mechanism-aware benchmark of 296 bilingual questions. The benchmark targets four structural skills central to real research: following multi-hop evidence chains, verifying claims across sources, re-ordering fragmented information...
| Authors | Shuoling Liu, Zhiquan Tan, Kun Yi et al. |
|---|---|
| Primary category | cs.LG |
| Published | 26 March 2026 |
| Last updated at source | 29 April 2026 |
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