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cs.CV2026
CV-DCLR: Causal-Visual Dynamic Label Refinement for Robust Zero-Shot Learning
Can Wang, Jiangnan Li, Mingyu Li +4
Zero-Shot Learning (ZSL) facilitates knowledge transfer via shared semantic spaces. However, a critical bottleneck in this paradigm is Semantic Entanglement, where visual represent…
cs.CV2026
Dynamic Visual-semantic Alignment for Zero-shot Learning with Ambiguous Labels
Jiangnan Li, Linqing Huang, Xiaowen Yan +3
Zero-shot learning (ZSL) aims to recognize unseen classes without visual instances. However, existing methods usually assume clean labels, overlooking real-world label noise and am…
cs.CV2026
CLIP-driven Zero-shot Learning with Ambiguous Labels
Jinfu Fan, Jiangnan Li, Xiaowen Yan +3
Zero-shot learning (ZSL) aims to recognize unseen classes by leveraging semantic information from seen classes, but most existing methods assume accurate class labels for training…