We present a continuous diffusion model for language modeling that incorporates the geometry of the underlying categorical distribution.

We propose the Multi-Reward Optimization (MRO) approach, which enhances token correlation during the denoising process in diffusion language models, improving reasoning performance and sampling efficiency.

We propose the delayed KV-Cache for diffusion language models.