rCM & Causal-rCM: Leading and Unified Algorithms/Infrastructures for Bidirectional/Autoregressive Video Diffusion Distillation at Scale
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Updated
Jun 25, 2026 - Python
rCM & Causal-rCM: Leading and Unified Algorithms/Infrastructures for Bidirectional/Autoregressive Video Diffusion Distillation at Scale
[arXiv 2026] This is the official PyTorch implementation of "MeanFlowNFT: Bringing Forward-Process RL to Average-Velocity Generators".
[RSS 2026] LPS: Latent Policy Steering through One-Step Flow Policies.
Unofficial PyTorch implementation of "Mean Flows for One-step Generative Modeling" (2025). Extends the framework to Edge-to-Image generation with Multi-scale Edge Encoder and 1-NFE sampling.
Interactive dependency-free lab on flow matching, rectified flow & MeanFlow one-step generation
DDPM, DDIM, GAN and MeanFlow implemented from scratch and compared under optimal-transport metrics — DDIM at 100 steps beats DDPM at 1000, and MeanFlow reaches competitive quality in a single network evaluation.
An implementation of Flow Matching based models
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