# Observable Patterns Are Not Explanations: A Causal-Geometric Analysis of Latent Reasoning Models

Authors: Darpan Aswal, Thomas Palmeira Ferraz, Yongxin Zhou, Maxime Peyrard.

Compares Coconut and CODI with controls lacking their proposed reasoning recurrence or curriculum. Finds that decodable patterns can also appear in controls, while interventions reveal varying causal use of latent states concentrated in low-dimensional directions.

First public: 2026-06-10.
ArXiv initial submission: 2026-06-10.

[Original paper](https://arxiv.org/abs/2606.12689) · [Reading-list entry](https://latent-implicit-thinking.github.io/papers/2606.12689/)
[Preprint BibTeX](https://latent-implicit-thinking.github.io/papers/2606.12689/citation.bib) · [Preprint CSL-JSON](https://latent-implicit-thinking.github.io/papers/2606.12689/citation.csl.json) · [JSON record](https://latent-implicit-thinking.github.io/papers/2606.12689/record.json)

## Approaches

- [Continuous-state reasoning](https://latent-implicit-thinking.github.io/topics/continuous-states/): Use vectors—lists of numbers—to carry intermediate reasoning from one step to the next, instead of selecting a text token at every step. Some methods use the model's hidden states; others combine several candidate token representations.
- [Analysis and evaluation](https://latent-implicit-thinking.github.io/topics/implicit-reasoning-evaluation/): Measure how well these methods work, investigate what their internal computation does, and identify where they fail. This includes experiments, studies of model internals, and mathematical results.

Summary and categories are editorial. Read the original paper to verify claims and limitations. A citation to a paper does not, by itself, establish that a later method builds on it.

Reading-list version 0.9.5; literature checked through 2026-10-18.