Tag
HyperFlow is an open-source 8-step LoRA that uses data-free flow self-distillation to reduce video generation steps from 49 to 8 in MiniMax-H3, achieving significant speedup while maintaining quality.
This paper introduces OPTD, an on-policy transition distillation method with consistency-guided adaptive compression for few-step diffusion language models, improving quality-efficiency trade-offs across four reasoning and code-generation benchmarks.
SE(3)-MeanFlow introduces a few-step generative framework for protein backbone generation on Lie groups, extending MeanFlow to SE(3) with closed-form average-velocity training targets and a rectification-based post-training that matches or exceeds flow-matching baselines at reduced sampling steps.
OPSD-V improves few-step autoregressive video diffusion models by using real long-video data as temporal context during training, providing dense trajectory-level supervision that enhances visual quality and motion dynamics without altering inference mechanisms.
Proposes Flow-Map GRPO, an online RL post-training framework for deterministic few-step flow-map generators, introducing Anchored Stochastic Flow Map Composition (ASFMC) to enable stochastic optimization without altering original model parameterization. Experiments on FLUX-based MeanFlow and sCM show improvement across reward-based, perceptual, and task-level metrics.
A LoRA that adapts Ideogram 4 to generate high-quality images in as few as 2 steps without CFG, using a novel continuous turbo training method.
Alibaba released Qwen-Image-Flash, a few-step distilled model for fast, high-quality text-to-image generation and instruction-guided editing, leveraging data composition, teacher guidance, and task mixture.
Causal Forcing++ presents a novel causal consistency distillation method for frame-wise autoregressive video generation, achieving state-of-the-art quality with reduced latency and training cost.