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cs.CV2026
Learning to Look Again: Loss-Gap Supervision for Free-form Crop Routing in Vision-Language Models
Jinchang Zhu, Rong Fu, Yi Ding +3
Vision-language models (VLMs) fail many detail-centric questions for a concrete reason: the answer is visible in the image, yet lost after the image is compressed into a low-resolu…
cs.CV2025★ 2 cited
CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive Survey
Jindong Li, Yongguang Li, Yali Fu +4
As machine learning evolves, domain generalization (DG) and domain adaptation (DA) have become crucial for enhancing model robustness across diverse environments. Contrastive Langu…
cs.CV2025
Beyond Retraining: Training-Free Unknown Class Filtering for Source-Free Open Set Domain Adaptation of Vision-Language Models
Yongguang Li, Jindong Li, Qi Wang +4
Vision-language models (VLMs) have gained widespread attention for their strong zero-shot capabilities across numerous downstream tasks. However, these models assume that each test…