AINeutralarXiv – CS AI · 5h ago6/10
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The Geometry of Representational Failures in Vision Language Models
Researchers have identified mechanistic explanations for why Vision-Language Models fail at multi-object visual tasks by analyzing the geometric structure of internal representations. By extracting and steering "concept vectors" in open-weight VLMs, they discovered that geometric overlap between these vectors correlates directly with specific error patterns, providing a quantitative framework for understanding representational failures.