AI RESEARCH
Active Exploring like a Pigeon: Reinforcing Spatial Reasoning via Agentic Vision-Language Models
arXiv CS.CV
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ArXi:2606.02459v1 Announce Type: new Enabling Vision-Language Models (VLMs) to perform spatial reasoning remains challenging. Existing approaches treat VLMs as passive observers, which is difficult for real-world applications. Moreover, reinforcement learning methods rely on sparse rewards, limiting their effectiveness for complex reasoning tasks. Inspired by pigeons' building and exploiting cognitive maps for navigation, we propose a novel agentic pipeline for spatial reasoning. First, we