# Beyond Chains of Thought: Benchmarking Latent-Space Reasoning Abilities in Large Language Models

Authors: Thilo Hagendorff, Sarah Fabi.

Encodes the answer in the language of the model's first response token, forcing a choice before any written explanation. Also tests whether successful answers could come from simple heuristics.

First public: 2025-04-14.
ArXiv initial submission: 2025-04-14.

[Original paper](https://arxiv.org/abs/2504.10615) · [Reading-list entry](https://latent-implicit-thinking.github.io/papers/2504.10615/)
[Preprint BibTeX](https://latent-implicit-thinking.github.io/papers/2504.10615/citation.bib) · [Preprint CSL-JSON](https://latent-implicit-thinking.github.io/papers/2504.10615/citation.csl.json) · [JSON record](https://latent-implicit-thinking.github.io/papers/2504.10615/record.json)

## Approaches

- [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.