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ToolSciVer: Multimodal Scientific Claim Verification with Visual Tool Augmented Reinforcement Learning

arXiv cs.CL · 2026-07-20 Cached

This paper introduces ToolSciVer, the first tool-augmented framework for multimodal scientific claim verification (MSCV), which equips a VLM with type-aware visual tools and trains the policy using GRPO to achieve superior performance on SciVer and MuSciClaims datasets across multiple model families.

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