AI RESEARCH
TextLDM: Language Modeling with Continuous Latent Diffusion
arXiv CS.CL
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ArXi:2605.07748v1 Announce Type: new Diffusion Transformers (DiT) trained with flow matching in a VAE latent space have unified visual generation across images and videos. A natural next step toward a single architecture for both generation (visual synthesis) and understanding (text generation) is to apply this framework to language modeling. We propose TextLDM, which transfers the visual latent diffusion recipe to text generation with minimal architectural modification.