How Does Reasoning Become Implicit? Uncovering the Dynamics of Chain-of-Thought Internalization

Latent reasoning replaces explicit chain-of-thought (CoT) with continuous states, yet how this transition reorganizes reasoning remains unclear. We study this internalization process through a unified mechanistic framework spanning training-time formation and inference-time function, and apply it to CODI and Coconut as two representative latent-reasoning paradigms. We find that internalization yields a strongly positionally asymmetric latent process, including pronounced even–odd organization and training-time reversals of positional bias. Despite this reorganization, latent reasoning retains task-relevant alignment with explicit CoT while following a distinct intermediate trajectory. At inference, latent-state contributions are recurrently interdependent and strongly conditioned on the surrounding trajectory. Finally, the explicit–latent reliability gap grows sharply with reasoning depth, while failed latent trajectories exhibit weaker stepwise semantic ordering and more diffuse causal organization across states. Together, these results show that reasoning internalization is not simply the direct transfer of explicit CoT into a hidden trajectory. The central mechanistic challenge for better reasoning internalization is therefore how task-relevant computation is organized across latent states and coordinated into reliable reasoning.