Flow Matching Requirements for Effective Latent Reasoning in LLMs

Effective latent reasoning requires continuous-space thought processes that are useful, diverse, explainable, refinable via inference compute, and more efficient than explicit chain-of-thought. Flow matching in learned latent spaces is proposed as the optimal method to avoid current pitfalls like shortcut learning or simple CoT distillation.