ToolGate: Token-Efficient Pre-Call Control for Tool-Augmented Vision-Language Agents 事件

ToolGate: Token-Efficient Pre-Call Control for Tool-Augmented Vision-Language Agents arXiv:2606.03054v1 Announce Type: new Abstract: Tool-augmented vision-language agents can acquire external perceptual evidence through OCR, detection, segmentation, and other tools, but executing every proposed tool call is costly and sometimes unnecessary. We study the pre-call control problem: after a ReAct-style VLM agent proposes a perceptual tool call, should the call be executed, or skipped before its out