Return
Data-efficient generalization for zero-shot composed image retrieval
DOI:10.1016/j.patcog.2026.113187.png)
Abstract
En 中文
• Observe modality discrepancy and distribution shift issue in ZS-CIR task • Enhance pseudo-word token with linguistic semantics • Excavate zero-shot capability of VLMs with novel loss functions • Achieve superior performance on four benchmarks with less training data • Achieve an optimal balance between training and inference cost
Journal
IF:
7.6
Papers:
1.3W
Citations:
4.5W

