ReTool-Video: Recursive Tool-Using Video Agents with Meta-Augmented Tool Grounding
Xiao Liu, Nayu Liu, Junnan Zhu, Ruirui Chen, Guohui Xiang, Changjian Wang, Kaiwen Wei, Rongzhen Li, Jiang Zhong

TL;DR
ReTool-Video introduces a recursive, tool-augmented approach with an extensive meta-tool library to enhance complex video reasoning and understanding.
Contribution
It presents a novel recursive method and a large, extensible meta-tool library for improved compositional and fine-grained video reasoning.
Findings
ReTool-Video outperforms strong baselines on multiple benchmarks.
Recursive grounding improves stability in complex video tasks.
Meta tools enable diverse multimodal reasoning scenarios.
Abstract
Video understanding requires active evidence seeking, motivating tool-augmented video agents for temporal reasoning, cross-modal understanding, and complex question answering. Existing video agents have improved video reasoning with retrieval, memory, frame inspection, and verifier tools, but they still face two limitations: (1) a coarse tool space that lacks fine-grained operations for compositional reasoning; and (2) a flat action space that forces high-level video intents into primitive executable tool calls. In this paper, we address these challenges with two complementary designs. First, we construct a MetaAug-Video Tool Library (MVTL), an extensible tool library with 134 registered tools, including 26 base tools for general multimodal signal processing and 108 meta tools for filtering, aggregation, reranking, formatting, and other intermediate-result operations. MVTL supports…
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