Interpreting Latent CoT Reasoning as Dynamical Systems
Recent latent reasoning methods, such as CODI and COCONUT, face a fundamental interpretability problem: they maintain multiple superimposed candidate traces in the hidden space at each step, unlike explicit- CoT, which follows a single transparent reasoning trace. Existing mechanistic methods show compression, shortcuts, and superposition without explaining how reasoning evolves across latent steps. To address this gap, we model latent token sequences as trajectories in representation space and apply dynamical systems analysis to characterize the evolution of reasoning. Using quantitative measures, such as step-to-step change, direction consistency, and Lyapunov sensitivity, alongside qua...
| Authors | Sabari Iyyappan Duraipandian, Shreya Sanjay Boyane, Manju Nagesh et al. |
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| Primary category | cs.AI |
| Published | 20 June 2026 |
| Last updated at source | 20 June 2026 |
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