380 citations · 504 across the 16 of their papers we have counts for
3 papers · 1 filter
Domain Recentering and Confidence-Weighted Prior Calibration for Vision-Language Models
Youngeun Seol, Jimin Shin, Heeseo Yoon +1
Vision-language models such as CLIP achieve strong zero-shot classification, yet under distribution shift, visual embeddings drift from fixed text embeddings. Training-free calibra…
Enhancing Alignment for Unified Multimodal Models via Semantically-Grounded Supervision
Jiyeong Kim, Yerim So, Hyesong Choi +2
Unified Multimodal Models (UMMs) have emerged as a promising paradigm that integrates multimodal understanding and generation within a unified modeling framework. However, current…
CLIP-RD: Relational Distillation for Efficient CLIP Knowledge Distillation
Jeannie Chung, Hanna Jang, Ingyeong Yang +2
Contrastive Language-Image Pre-training (CLIP) demonstrates strong zero-shot generalization, but due to substantial computational and memory costs, distillation into lightweight mo…