.png){kind=icon}
Return
Partial label zero-shot learning with semantic mining and instance–label alignment
.png){kind=icon}
PRE
AI
DOI：10.1016/j.engappai.2026.114854.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• A new framework for ZSL with ambiguous labels. • A semantic mining block detects noisy labels by instance-label matching. • A partial zero-shot loss reduces noise and aligns embeddings.
Keywords:
Zero-shot learning
Semantic mining
Label noise
Embedding alignment
Instance-label matching
Journal
IF:
8
Papers:
5.7K
Citations:
3.5W
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSaveShareSaveDistribution and gradient constrained embedding model for zero-shot learning with fewer seen samples
OAAI
OAAIShareSaveShareSave
View more