RDM trains one-step generators via MMD on large batches and multi-encoder representations, achieving SOTA SW_r14 of 1.30 on ImageNet and distilling FLUX.2 to one-step with gains on GenEval and PickScore.
International Conference on Machine Learning , year=
4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 4verdicts
UNVERDICTED 4representative citing papers
Pepti-drift performs a single antigen-conditioned drift in peptide latent space to produce valid, diverse peptides with reduced toxicity and high efficiency compared to prior methods.
Hallucinations in diffusion models are driven by local intrinsic dimension instabilities on the manifold, which Intrinsic Quenching corrects by deflating it.
Alice v1 is an open video model that surpasses its teacher and closed-source systems like Veo3 and Sora2 in quality while running 7x faster through specialized distillation.
citing papers explorer
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Representation Distribution Matching for One-Step Visual Generation
RDM trains one-step generators via MMD on large batches and multi-encoder representations, achieving SOTA SW_r14 of 1.30 on ImageNet and distilling FLUX.2 to one-step with gains on GenEval and PickScore.
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Pepti-drift: Toxicity-Repulsive Drifting for Antigen-Conditioned Discrete Peptide Generation
Pepti-drift performs a single antigen-conditioned drift in peptide latent space to produce valid, diverse peptides with reduced toxicity and high efficiency compared to prior methods.
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Local Intrinsic Dimension Unveils Hallucinations in Diffusion Models
Hallucinations in diffusion models are driven by local intrinsic dimension instabilities on the manifold, which Intrinsic Quenching corrects by deflating it.
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Alice v1: Distillation-Enhanced Video Generation Surpassing Closed-Source Models
Alice v1 is an open video model that surpasses its teacher and closed-source systems like Veo3 and Sora2 in quality while running 7x faster through specialized distillation.