AI RESEARCH
Bridging Visual Representation and Reinforcement Learning from Verifiable Rewards in Large Vision-Language Models
arXiv CS.CV
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ArXi:2603.27375v1 Announce Type: new Reinforcement Learning from Verifiable Rewards (RLVR) has substantially enhanced the reasoning capabilities of large language models in abstract reasoning tasks. However, its application to Large Vision-Language Models (LVLMs) remains constrained by a structural representational bottleneck.