arXiv 2610.26216 · cs.CV · 2026-10-19
RoAR-VAE: Improving Latent Diffusability through Robust Prediction
Yang Yue, Fangyun Wei, Yitong Wang, Jinjing Zhao, Henry Zheng, Dong Chen, Gao Huang
Tsinghua-LeapLab
In latest · #286 Added on 2026-10-22
One-line takeaway
RoAR-VAE trains tokenizers so semantics and pixels remain recoverable from corrupted latents, making latents easier for diffusion models to learn.
RoAR-VAE 提出“稳健预测”原则：让被破坏的潜变量仍能恢复语义和图像，从而让潜空间更容易被扩散模型学习。
Read on arXiv PDF Hugging Face discussion Code
Topics & disciplines
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About this data
Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-22.
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