Making every tool call count: necessary tool-evidence path rewards for agentic vision-language models
Read the original at arxiv.org→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...
Original headline: "Making Every Tool Call Count: Necessary Tool-Evidence Path Rewards for Agentic Vision-Language Models"
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- Sep 4, 04:00 UTC arXiv cs.AI lead source Making Every Tool Call Count: Necessary Tool-Evidence Path Rewards for Agentic Vision-Language Models