The LaDiR framework integrates latent diffusion models with LLMs to overcome the limits of autoregressive decoding. It replaces linear token generation with iterative refinement in a continuous latent space. This allows the model to revisit and correct earlier reasoning steps. Practitioners can now explore diverse solution paths more efficiently than standard chain-of-thought methods.