mlsanityData to 7 Oct 2026

Typed Chain-of-Thought: A Curry-Howard Framework for Verifying LLM Reasoning

arXiv 2510.01069 ↗First posted 1 Oct 2025cs.AIcited by 3

On the map: LLM reasoning → Reasoning benchmarks and evaluation

Abstract (arXiv)

While Chain-of-Thought (CoT) prompting enhances the reasoning capabilities of large language models, the faithfulness of the generated rationales remains an open problem for model interpretability. We propose a novel theoretical lens for this problem grounded in the Curry-Howard correspondence, which posits a direct relationship between formal proofs and computer programs. Under this paradigm, a faithful reasoning trace is analogous to a well-typed program, where each intermediate step corresponds to a typed logical inference. We operationalise this analogy, presenting methods to extract and map the informal, natural language steps of CoT into a formal, typed proof structure. Successfully converting a CoT trace into a well-typed proof serves as a strong, verifiable certificate of its computational faithfulness, moving beyond heuristic interpretability towards formal verification. Our framework provides a methodology to transform plausible narrative explanations into formally verifiable programs, offering a path towards building more reliable and trustworthy AI systems.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 33 of its 49 references that are in the map. First posted on arXiv 1 Oct 2025.

Builds on

33 of 49 references.

Closest ancestors · 6

Same direction, newest first

  1. 2025Clarifying Before Reasoning: A Coq Prover with Structural Context3 Jul
  2. 2025Theorem-of-Thought: A Multi-Agent Framework for Abductive, Deductive, and Inductive Reasoning in Language Models8 Jun
  3. 2025Qwen3 Technical Report14 May
  4. 2024On the Diagram of Thought16 Sep
  5. 2022PAL: Program-aided Language Models18 Nov
  6. 2022ReAct: Synergizing Reasoning and Acting in Language Models6 Oct

Other references · 27

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  2. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,146
  3. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,601
  4. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,064
  5. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,155
  6. 2024OpenAI o1 System Cardcited by 1,220
  7. 2023Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Promptingcited by 1,081
  8. 2024Training Large Language Models to Reason in a Continuous Latent Spacecited by 763
  9. 2023Measuring Faithfulness in Chain-of-Thought Reasoningcited by 668
  10. 2025Reasoning Models Don't Always Say What They Thinkcited by 388
  11. 2025Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approachcited by 372
  12. 2025Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscationcited by 338
15 more
  1. 2024Alignment faking in large language modelscited by 316
  2. 2024Frontier Models are Capable of In-context Schemingcited by 252
  3. 2025Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safetycited by 222
  4. 2025Open Problems in Mechanistic Interpretabilitycited by 173
  5. 2025Chain-of-Thought Reasoning In The Wild Is Not Always Faithfulcited by 166
  6. 2025When Chain of Thought is Necessary, Language Models Struggle to Evade Monitorscited by 81
  7. 2023Beyond Chain-of-Thought, Effective Graph-of-Thought Reasoning in Language Modelscited by 51
  8. 2025CoT Red-Handed: Stress Testing Chain-of-Thought Monitoringcited by 49
  9. 2023The Expressive Power of Transformers with Chain of Thoughtcited by 47
  10. 2024Sabotage Evaluations for Frontier Modelscited by 45
  11. 2025Infrastructure for AI Agentscited by 40
  12. 2025Prover Agent: An Agent-Based Framework for Formal Mathematical Proofscited by 28
  13. 2025MA-LoT: Model-Collaboration Lean-based Long Chain-of-Thought Reasoning enhances Formal Theorem Provingcited by 24
  14. 2025How does Chain of Thought Think? Mechanistic Interpretability of Chain-of-Thought Reasoning with Sparse Autoencodingcited by 19
  15. 2025Out of Control -- Why Alignment Needs Formal Control Theory (and an Alignment Control Stack)cited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2024Proof of Thought : Neurosymbolic Program Synthesis allows Robust and Interpretable Reasoning
  2. 2026The Tell-Tale Trace: Detecting Reasoning Failures in LLMs Using Chain-of-Thought Dynamics
  3. 2025Hilbert: Recursively Building Formal Proofs with Informal Reasoning
  4. 2025Beyond Correctness: Exposing LLM-generated Logical Flaws in Reasoning via Multi-step Automated Theorem Proving
  5. 2022Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought
  6. 2025Can Large Language Models Learn Formal Logic? A Data-Driven Training and Evaluation Framework
  7. 2026What Was Said, Not What Was 'Thought': Type-6 Logic for CoT Verification
  8. 2025Safe: Enhancing Mathematical Reasoning in Large Language Models via Retrospective Step-aware Formal Verification