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VideoResearcher: Self-Improving Tool Design for Long-Video Understanding

arXiv · AI, language, vision and robotics · article · Sep 17, 2026 · UTC

Video agents have made substantial progress in long-video understanding. Yet effective video-agent systems require costly, time-consuming manual design and trial and error. Current self-improvement methods either refine low-impact prompts, recombine predefined micro-tools, or struggle with convergence in harness optimization. To bridge this gap, we target high-impact video-tool with VideoResearcher, a training-free multi-agent framework that autonomously designs, tests, and refines tools for video understanding, like a human researcher. VideoResearcher operates through dual Solving and Evolvin

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Evidence & attribution

First collected: 2026-09-19T20:28:21.856Z. This is not the publication date.