LaDi-RL: Latent Diffusion Reasoning Prevents Entropy Collapse in Reinforcement Learning

In three linesLaDi-RL optimizes LLM reasoning via RL in latent space using diffusion. Instead of optimizing token sequences, the method generates latent reasoning trajectories through iterative denoising. It solves credit assignment (rewards observed after decoding) via hierarchical latent-text rollouts. Gains: +9.4% code generation, +5.7% math reasoning on pass@1.

Summary generated by Claude — human-verified