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cs.CV2026
End-to-End Training for Unified Tokenization and Latent Denoising
Shivam Duggal, Xingjian Bai, Zongze Wu +5
Latent diffusion models (LDMs) enable high-fidelity synthesis by operating in learned latent spaces. However, training state-of-the-art LDMs requires complex staging: a tokenizer m…
cs.CV2025
Cycle Consistency as Reward: Learning Image-Text Alignment without Human Preferences
Hyojin Bahng, Caroline Chan, Fredo Durand +1
Measuring alignment between language and vision is a fundamental challenge, especially as multimodal data becomes increasingly detailed and complex. Existing methods often rely on…