AI RESEARCH
Riemannian MeanFlow
arXiv CS.LG
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ArXi:2602.07744v3 Announce Type: replace Diffusion and flow models have become the dominant paradigm for generative modeling on Riemannian manifolds, with successful applications in protein backbone generation and DNA sequence design. However, these methods require tens to hundreds of neural network evaluations at inference time, which can become a computational bottleneck in large-scale scientific sampling workflows. We