A Step in the Right Place: Understanding and Optimizing Timestep Placement in Continuous Diffusion Language Models
It is demonstrated that changing timestep placement alone can substantially alter the final latent representations and thereby affect the decoded token distributions and establish timestep placement as a practical means of improving the quality-efficiency trade-off in continuous diffusion language models.