[2603.20185] VideoSeek: Long-Horizon Video Agent with Tool-Guided Seeking

Computer Science > Computer Vision and Pattern Recognition arXiv:2603.20185 (cs) [Submitted on 20 Mar 2026] Title:VideoSeek: Long-Horizon Video Agent with Tool-Guided Seeking Authors:Jingyang Lin, Jialian Wu, Jiang Liu, Ximeng Sun, Ze Wang, Xiaodong Yu, Jiebo Luo, Zicheng Liu, Emad Barsoum View a PDF of the paper titled VideoSeek: Long-Horizon Video Agent with Tool-Guided Seeking, by Jingyang Lin and 8 other authors View PDF HTML (experimental) Abstract:Video agentic models have advanced challenging video-language tasks. However, most agentic approaches still heavily rely on greedy parsing over densely sampled video frames, resulting in high computational cost. We present VideoSeek, a long-horizon video agent that leverages video logic flow to actively seek answer-critical evidence instead of exhaustively parsing the full video. This insight allows the model to use far fewer frames while maintaining, or even improving, its video understanding capability. VideoSeek operates in a think-act-observe loop with a well-designed toolkit for collecting multi-granular video observations. This design enables query-aware exploration over accumulated observations and supports practical video understanding and reasoning. Experiments on four challenging video understanding and reasoning benchmarks demonstrate that VideoSeek achieves strong accuracy while using far fewer frames than prior video agents and standalone LMMs. Notably, VideoSeek achieves a 10.2 absolute points improvement on L...