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News/Making Every Tool Call Count: Necessary Tool-Evidence Path Rewards for Agentic Vision-Language Models
arxiv
PublishedSeptember 4, 2026 at 4:00 AM
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Making Every Tool Call Count: Necessary Tool-Evidence Path Rewards for Agentic Vision-Language Models

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arXiv:2609.03493v1 Announce Type: new Abstract: Modern vision-language models (VLMs) can directly answer many image-grounded questions, yet they often struggle with complex queries requiring fine-grained visual details or external knowledge. To acquire this missing evidence, agentic VLMs invoke tool

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