# Dynamic K-Head: Difficulty-Supervised Budget Selection for Continuous Latent Reasoning

Authors: Ying Li, Yuqi Chen, Sixuan Li, Yunfeng Cai.

Predicts from the question how many continuous reasoning updates to perform. Evaluates total cost including latent updates, special tokens, and any written continuation rather than counting latent steps alone.

First public: 2026-10-13.
ArXiv initial submission: 2026-10-13.

[Original paper](https://arxiv.org/abs/2610.17679) · [Reading-list entry](https://latent-implicit-thinking.github.io/papers/2610.17679/)
[Preprint BibTeX](https://latent-implicit-thinking.github.io/papers/2610.17679/citation.bib) · [Preprint CSL-JSON](https://latent-implicit-thinking.github.io/papers/2610.17679/citation.csl.json) · [JSON record](https://latent-implicit-thinking.github.io/papers/2610.17679/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.

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.