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Sen Fang, Yalin Feng, Yanxin Zhang, Yihao Quan, Juyi Lin, Yifan Shen, Ziwei Dong, Sisong Bei, Dimitris N. Metaxas
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ResearcharXiv cs.CV
RAC: Rectified Flow Auto Coder
arXiv:2603.05925v2 Announce Type: replace
Abstract: In this paper, we propose a Rectified Flow Auto Coder (RAC) inspired by Rectified Flow to replace the traditional VAE: 1. It achieves multi-step decoding by applying the decoder to flow timesteps. Its decoding path is straight and correctable, enabling step-by-step refinement. 2. The model inherently supports bidirectional inference, where the decoder serves as the encoder through time reversal (hence Coder rather than encoder or decoder), reducing parameter count by nearly 41%. 3. This generative decoding method improves generation quality since the model can correct latent variables along the path, partially addressing the reconstruction--generation gap. Experiments show that RAC achieves a Pareto improvement over SOTA VAEs, where even a 10$\times$ parameter-reduced decoder exceeds full-scale VAE performance in both reconstruction and generation quality, validating the effectiveness of our approach.
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This story was published by arXiv cs.CV and written by Sen Fang, Yalin Feng, Yanxin Zhang, Yihao Quan, Juyi Lin, Yifan Shen, Ziwei Dong, Sisong Bei, Dimitris N. Metaxas. SyncAI.news shows a preview; the complete article is on the publisher's site.
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