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cs.CV2026
DPA: Decoupling Product-Agnostic Anomaly Representations for Zero-shot Anomaly Generation
Hang Yao, Yansheng Fu, Ming Liu +4
Industrial anomaly detection benefits from anomaly samples, yet newly deployed products typically provide only normal images, making anomaly samples difficult to collect. Zero-shot…
cs.CV2026
Position Rebinding Cache Reuse: Replay-Free Visual Revisiting for Interleaved Multimodal Reasoning
Mengzhao Wang, Yanli Ji, Wangmeng Zuo +2
Interleaved multimodal reasoning improves visual grounding by revisiting visual evidence during multi-step generation, yet existing methods typically rely on token replay, repeated…
cs.CV2023★ 1 cited
Learning with Noisy Labels Using Collaborative Sample Selection and Contrastive Semi-Supervised Learning
Qing Miao, Xiaohe Wu, Chao Xu +4
Learning with noisy labels (LNL) has been extensively studied, with existing approaches typically following a framework that alternates between clean sample selection and semi-supe…