AI RESEARCH
How to Train Your Latent Diffusion Language Model Jointly With the Latent Space
arXiv CS.CL
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ArXi:2605.07933v1 Announce Type: new Latent diffusion models offer an attractive alternative to discrete diffusion for non-autoregressive text generation by operating on continuous text representations and denoising entire sequences in parallel. The major challenge in latent diffusion modeling is constructing a suitable latent space. In this work, we present the Latent Diffusion Language Model (LDLM), in which the latent encoder, diffusion model, and decoder are trained jointly.