research
LaDiR uses latent diffusion to improve LLM reasoning beyond autoregressive decoding
Researchers propose LaDiR (Latent Diffusion Reasoner), a framework that combines variational autoencoders and latent diffusion models to improve LLM reasoning. The approach encodes reasoning steps into continuous latent representations, enabling iterative refinement and parallel generation of diverse solutions beyond traditional autoregressive decoding.