3 papers
cs.CV2026
Unifying Contrastive and Generative Objectives for Visual Understanding and Text-to-Image Generation
Chao Li, Tianhong Li, Sai Vidyaranya Nuthalapati +9
Unifying text-image contrastive learning and text-to-image (T2I) generation in a single end-to-end model is challenging because the two objectives demand opposing masking regimes:…
cs.CV2025
Single-Teacher View Augmentation: Boosting Knowledge Distillation via Angular Diversity
Seonghoon Yu, Dongjun Nam, Dina Katabi +1
Knowledge Distillation (KD) aims to train a lightweight student model by transferring knowledge from a large, high-capacity teacher. Recent studies have shown that leveraging diver…
cs.CV2024
Return of Unconditional Generation: A Self-supervised Representation Generation Method
Tianhong Li, Dina Katabi, Kaiming He
Unconditional generation -- the problem of modeling data distribution without relying on human-annotated labels -- is a long-standing and fundamental challenge in generative models…