ResearStudio: A Human-intervenable Framework for Building Controllable Deep Research Agents (2025.emnlp-demos)
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| Challenge: | Existing deep-research agents run in a 'fire-and-forget' mode, with no way to fix errors or add expert knowledge during execution. |
| Approach: | They propose to use a planner-executor to write every step to a live 'plan-as-document' a fast communication layer streams each action, file change, and tool call to . web interface. |
| Outcome: | The proposed framework surpasses OpenAI’s DeepResearch and Manus in the GAIA benchmark. |
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