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cs.CV2026
Focus and Supplement: Dual-Enhanced Vision Transformer for Multi-Class Anomaly Classification
Xurui Li, Enjie Xu, Chenzhou Li +4
Multi-class anomaly classification in industrial vision remains challenging due to noisy/incomplete anomaly representations and the unknown number of anomaly classes. To overcome t…
cs.CL2026
Better and Worse with Scale: How Contextual Entrainment Diverges with Model Size
Dikshant Kukreja, Kshitij Sah, Gautam Gupta +5
Larger language models become simultaneously better and worse at handling contextual information -- better at ignoring false claims, worse at ignoring irrelevant tokens. We formali…