3 papers
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…
cs.LG2025
Divide-Then-Rule: A Cluster-Driven Hierarchical Interpolator for Attribute-Missing Graphs
Yaowen Hu, Wenxuan Tu, Yue Liu +5
Deep graph clustering (DGC) for attribute-missing graphs is an unsupervised task aimed at partitioning nodes with incomplete attributes into distinct clusters. Addressing this chal…