AI RESEARCH
Locating and Editing Figure-Ground Organization in Vision Transformers
arXiv CS.CV
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ArXi:2603.06407v1 Announce Type: new Vision Transformers must resolve figure-ground organization by choosing between completions driven by local geometric evidence and those favored by global organizational priors, giving rise to a characteristic perceptual ambiguity. We aim to locate where the canonical Gestalt prior convexity is realized within the internal components of BEiT. Using a controlled perceptual conflict based on synthetic shapes of darts, we systematically mask regions that equally admit either a concave completion or a convex completion.