Robust Representation Consistency Model via Contrastive Denoising
Published in The Thirteenth International Conference on Learning Representations (ICLR 2025), 2025
This paper proposes a robust representation consistency model that leverages contrastive denoising to learn robust and consistent representations.
Recommended citation: Jiachen Lei, Julius Berner, Jiongxiao Wang, Zhongzhu Chen, Zhongjia Ba, Kui Ren, Jun Zhu, Anima Anandkumar. (2025). "Robust Representation Consistency Model via Contrastive Denoising." ICLR 2025.
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