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arXiv Computer Vision By Peipei Li, Shuhan Xia, Shengyang Liu, Zekun Li, Ran He

MM-VeriAgent: Learning to Use Extensive Tools to Verify Multimodal Misinformation with Reinforcement Learning

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MM-VeriAgent is a reinforcement‑learning framework that learns to verify multimodal misinformation by leveraging a specialized toolkit called MM-VeriTools. The toolkit encapsulates the strongest models for textual, visual, and cross‑modal forgery analysis as callable tools with a unified interface. To improve training efficiency, the authors introduce a Tool‑Execution Cache that pre‑executes candidate tool calls and reuses cached outputs, resulting in substantial accuracy gains on MMFakeBench and reduced online tool executions during training.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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