AI RESEARCH
Bad Seeing or Bad Thinking? Rewarding Perception for Vision-Language Reasoning
arXiv CS.CV
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ArXi:2605.14054v1 Announce Type: cross Achieving robust perception-reasoning synergy is a central goal for advanced Vision-Language Models (VLMs). Recent advancements have pursued this goal via architectural designs or agentic workflows. However, these approaches are often limited by static textual reasoning or complicated by the significant compute and engineering burden of external agentic complexity. Worse, this heavy investment does not yield proportional gains, often witnessing a "seesaw effect" on perception and reasoning.