S1-DeepResearch: Beyond Search, Toward Real-World Long-Horizon Research Agents
Deep research agents aim to solve complex knowledge-intensive tasks through long-horizon planning, evidence gathering, reasoning, and report generation. While recent progress in search agents has demonstrated strong capabilities in information retrieval and answer verification, most existing training datasets remain search-centric, focusing primarily on closed-ended question answering and information localization. As a result, they mainly train information-seeking behavior while providing limited coverage of key deep research capabilities, including evidence integration, knowledge synthesis, planning, file understanding, and structured report generation. In this work, we propose a unified...
| Authors | Yao Dong, Xinglin Xiao, Liwei Dong et al. |
|---|---|
| Primary category | cs.AI |
| Published | 13 June 2026 |
| Last updated at source | 13 June 2026 |
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