FlowLM: Few-Step Language Modeling via Diffusion-to-Flow Adaptation

In three linesFlowLM converts pre-trained diffusion language models into flow matching models via efficient fine-tuning. By realigning curved diffusion trajectories into straight-line flows, FlowLM achieves high-quality few-step text generation rivaling 2,000-step diffusion sampling. Performance saturation reached with half the training epochs compared to training from scratch.

Summary generated by Claude — human-verified