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cs.LG2025
NeuCLIP: Efficient Large-Scale CLIP Training with Neural Normalizer Optimization
Xiyuan Wei, Chih-Jen Lin, Tianbao Yang
Accurately estimating the normalization term (also known as the partition function) in the contrastive loss is a central challenge for training Contrastive Language-Image Pre-train…
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…