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cs.CV2026
Interpretability-Guided Soft Pruning of Attention Heads in Vision Transformers
Kamil Książek, Piotr Suszyński, Michał Jan Włodarczyk +2
Vision foundation models, such as DINOv2, learn highly expressive representations but rely on massive, opaque architectures that demand substantial computational power and memory.…
cs.CV2026
Local Intrinsic Dimension Unveils Hallucinations in Diffusion Models
Bartlomiej Sobieski, Matthew Tivnan, Dawid Płudowski +4
Diffusion models are prone to generating structural hallucinations - samples that match the statistical properties of the training data yet defy underlying structural rules, result…