Summary

This repository serves as a comprehensive, regularly updated paper list dedicated to Latent Chain-of-Thought (CoT) reasoning. It addresses the limitations of traditional language-based AI reasoning by exploring methods that leverage abstract, non-language "latent spaces" for thought processes. This paradigm shift promises richer representations of complex ideas, reduced inference latency, and more flexible, human-like AI cognition, targeting researchers and engineers developing advanced reasoning models.

How It Works

Latent CoT reasoning fundamentally shifts AI thought processes from discrete language tokens to continuous, abstract latent spaces. This approach allows models to capture complex, non-verbal reasoning patterns more effectively than purely symbolic manipulation. Key advantages include richer thought representation, enabling deeper understanding, and reduced latency due to higher information density and less reliance on token decoding, ultimately facilitating more efficient and powerful AI reasoning capabilities.

Quick Start & Requirements

This repository functions as a curated collection of research papers and supplementary resources, rather than a deployable software package. Users can access the listed papers via provided PDF links and explore associated code repositories where available. No direct installation or execution commands are applicable, and no specific hardware or software prerequisites are listed for the repository itself.

Highlighted Details

• Features a regularly updated survey on Latent CoT Reasoning, with the primary survey paper available on arXiv (https://arxiv.org/abs/2505.16782).
• Organizes research into key thematic areas: Token-wise Strategies, Internal Mechanisms, Structural CoT, Representational CoT, Analysis and Interpretability, and Applications and Future Directions.
• Provides direct links to numerous research papers (PDFs) and associated code repositories, detailing various latent reasoning techniques.
• Curates links to other relevant external resources, such as Awesome-Efficient-Reasoning and awesome-llm-implicit-reasoning, for broader context.

Maintenance & Community

Launched in February 2025 and actively updated, the repository encourages community contributions for missing papers. It links to related curated resources but does not specify direct community channels like Discord or Slack, nor does it list notable contributors or sponsorships.

Licensing & Compatibility

The repository itself does not specify a license. Users must adhere to the licensing terms of the individual research papers and code repositories linked within, which may vary. Compatibility for commercial use depends entirely on the licenses of the cited works.

Limitations & Caveats

As a paper list, this repository does not offer executable code, direct benchmarks, or a software framework. Its scope is strictly limited to Latent CoT reasoning research, and it is an evolving resource with ongoing updates. Users must consult individual papers for specific implementation details, limitations, and performance claims.