3 papers
cs.CV2026
Breaking the Limits of Open-Weight CLIP: An Optimization Framework for Self-supervised Fine-tuning of CLIP
Anant Mehta, Xiyuan Wei, Xingyu Chen +1
CLIP has become a cornerstone of multimodal representation learning, yet improving its performance typically requires a prohibitively costly process of training from scratch on bil…
cs.CV2025
AdFair-CLIP: Adversarial Fair Contrastive Language-Image Pre-training for Chest X-rays
Chenlang Yi, Zizhan Xiong, Qi Qi +5
Contrastive Language-Image Pre-training (CLIP) models have demonstrated superior performance across various visual tasks including medical image classification. However, fairness c…
cs.LG2025
Model Steering: Learning with a Reference Model Improves Generalization Bounds and Scaling Laws
Xiyuan Wei, Ming Lin, Fanjiang Ye +4
This paper formalizes an emerging learning paradigm that uses a trained model as a reference to guide and enhance the training of a target model through strategic data selection or…