Chain-of-Thought & Reasoning Reading List

Curated by Mouhssine Rifaki | Stanford Electrical Engineering | Last updated August 2026

Key papers on chain-of-thought prompting and reasoning in LLMs — from eliciting step-by-step traces to self-consistency and verification.

Chain-of-Thought & Reasoning: 10 key papers

1. Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
   Wei et al. arXiv 2022.
2. Self-Consistency Improves Chain of Thought Reasoning in Language Models
   Wang et al. arXiv 2022.
3. Large Language Models are Zero-Shot Reasoners
   Kojima et al. arXiv 2022.
4. Least-to-Most Prompting Enables Complex Reasoning in Large Language Models
   Zhou et al. arXiv 2022.
5. Tree of Thoughts: Deliberate Problem Solving with Large Language Models
   Yao et al. arXiv 2023.
6. Graph of Thoughts: Solving Elaborate Problems with Large Language Models
   Besta et al. arXiv 2023.
7. Self-Refine: Iterative Refinement with Self-Feedback
   Madaan et al. arXiv 2023.
8. Automatic Chain of Thought Prompting in Large Language Models
   Zhang et al. arXiv 2022.
9. Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters
   Wang et al. arXiv 2022.
10. Chain-of-Thought Reasoning Without Prompting
    Wang and Zhou. arXiv 2024.

Related reading lists

• Reasoning in LLMs
• In-Context RL & Prompting
• Prompt Optimization & In-Context Learning for LLMs
• LLM Agents & Tool-Augmented Language Models
• Graph Neural Networks & Message Passing
• Causal Inference & RL
• Monte Carlo Tree Search
• Formal Verification & Neural Theorem Proving