mlsanityData to 7 Oct 2026

Large Language Model Guided Tree-of-Thought

arXiv 2305.08291 ↗First posted 15 May 2023cs.AI cs.CL cs.CVcited by 218

On the map: LLM reasoning → Test-time compute and efficient thinking

Abstract (arXiv)

In this paper, we introduce the Tree-of-Thought (ToT) framework, a novel approach aimed at improving the problem-solving capabilities of auto-regressive large language models (LLMs). The ToT technique is inspired by the human mind's approach for solving complex reasoning tasks through trial and error. In this process, the human mind explores the solution space through a tree-like thought process, allowing for backtracking when necessary. To implement ToT as a software system, we augment an LLM with additional modules including a prompter agent, a checker module, a memory module, and a ToT controller. In order to solve a given problem, these modules engage in a multi-round conversation with the LLM. The memory module records the conversation and state history of the problem solving process, which allows the system to backtrack to the previous steps of the thought-process and explore other directions from there. To verify the effectiveness of the proposed technique, we implemented a ToT-based solver for the Sudoku Puzzle. Experimental results show that the ToT framework can significantly increase the success rate of Sudoku puzzle solving. Our implementation of the ToT-based Sudoku solver is available on GitHub: urlhttps://github.com/jieyilong/tree-of-thought-puzzle-solver.

Key facts. Cited by 218 papers in the map (data through 7 Oct 2026). Placed in Test-time compute and efficient thinking, one of 17 directions in LLM reasoning. Builds on 0 of its 36 references that are in the map. First posted on arXiv 15 May 2023.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 43; 2024: 61; 2025: 85; 2026: 29.

218 papers.

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  1. 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 1,908
  2. 2023Graph of Thoughts: Solving Elaborate Problems with Large Language Modelscited by 873
  3. 2024A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applicationscited by 428
  4. 2023Alphazero-like Tree-Search can Guide Large Language Model Decoding and Trainingcited by 291
  5. 2024Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Modelcited by 258
  6. 2025Large Language Model Agent: A Survey on Methodology, Applications and Challengescited by 194
  7. 2023Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Futurecited by 184
  8. 2025Multimodal Chain-of-Thought Reasoning: A Comprehensive Surveycited by 176
  9. 2024A Roadmap to Pluralistic Alignmentcited by 175
  10. 2025Hierarchical Reasoning Modelcited by 167
  11. 2023LM vs LM: Detecting Factual Errors via Cross Examinationcited by 155
  12. 2023Shifting Attention to Relevance: Towards the Predictive Uncertainty Quantification of Free-Form Large Language Modelscited by 147
38 more
  1. 2025Dynamic Cheatsheet: Test-Time Learning with Adaptive Memorycited by 146
  2. 2024Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizingcited by 123
  3. 2024LLM Multi-Agent Systems: Challenges and Open Problemscited by 119
  4. 2023Cumulative Reasoning with Large Language Modelscited by 94
  5. 2024Chain of Preference Optimization: Improving Chain-of-Thought Reasoning in LLMscited by 94
  6. 2023Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Modelscited by 92
  7. 2023Can Knowledge Graphs Reduce Hallucinations in LLMs? : A Surveycited by 92
  8. 2025Multiagent Finetuning: Self Improvement with Diverse Reasoning Chainscited by 90
  9. 2024NavCoT: Boosting LLM-Based Vision-and-Language Navigation via Learning Disentangled Reasoningcited by 77
  10. 2025TreeRL: LLM Reinforcement Learning with On-Policy Tree Searchcited by 75
  11. 2025From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discoverycited by 74
  12. 2023Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generationcited by 73
  13. 2025Tree Search for LLM Agent Reinforcement Learningcited by 73
  14. 2023Unleashing the potential of prompt engineering for large language modelscited by 72
  15. 2024Reinforcement Learning Enhanced LLMs: A Surveycited by 69
  16. 2024StateFlow: Enhancing LLM Task-Solving through State-Driven Workflowscited by 65
  17. 2024Demystifying Chains, Trees, and Graphs of Thoughtscited by 63
  18. 2023PEARL: Prompting Large Language Models to Plan and Execute Actions Over Long Documentscited by 61
  19. 2025Multi-Agent Verification: Scaling Test-Time Compute with Multiple Verifierscited by 58
  20. 2023Let's Think Outside the Box: Exploring Leap-of-Thought in Large Language Models with Creative Humor Generationcited by 56
  21. 2025SRPO: Enhancing Multimodal LLM Reasoning via Reflection-Aware Reinforcement Learningcited by 53
  22. 2023Let Models Speak Ciphers: Multiagent Debate through Embeddingscited by 49
  23. 2023Tree-Planner: Efficient Close-loop Task Planning with Large Language Modelscited by 48
  24. 2026A Survey of Agentic Reasoning for Large Language Models: Towards Recursively Self-Improving and Collective Agentscited by 47
  25. 2024Puzzle Solving using Reasoning of Large Language Models: A Surveycited by 44
  26. 2025A Survey of Test-Time Compute: From Intuitive Inference to Deliberate Reasoningcited by 40
  27. 2023Teach AI How to Code: Using Large Language Models as Teachable Agents for Programming Educationcited by 38
  28. 2023Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RLcited by 37
  29. 2024Causal Language Modeling Can Elicit Search and Reasoning Capabilities on Logic Puzzlescited by 35
  30. 2025OctoNav: Towards Generalist Embodied Navigationcited by 33
  31. 2024Tool-Planner: Task Planning with Clusters across Multiple Toolscited by 32
  32. 2025PENCIL: Long Thoughts with Short Memorycited by 31
  33. 2023An In-depth Survey of Large Language Model-based Artificial Intelligence Agentscited by 30
  34. 2023Pangu-Agent: A Fine-Tunable Generalist Agent with Structured Reasoningcited by 30
  35. 2024Artificial Intelligence for Literature Reviews: Opportunities and Challengescited by 30
  36. 2023AutoHint: Automatic Prompt Optimization with Hint Generationcited by 29
  37. 2023Agent-OM: Leveraging LLM Agents for Ontology Matchingcited by 26
  38. 2023The Efficiency Spectrum of Large Language Models: An Algorithmic Surveycited by 25

50 most cited of 218 All 218 (JSON)

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  1. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Models
  2. 2026Domain-Specialized Tree of Thought through Plug-and-Play Predictors
  3. 2024Tree of Problems: Improving structured problem solving with compositionality
  4. 2026Policy-Guided Search on Tree-of-Thoughts for Efficient Problem Solving with Bounded Language Model Queries
  5. 2026Tree of Thoughts as a Classical Heuristic Search Problem: Formal Foundations and Design Patterns
  6. 2024Understanding When Tree of Thoughts Succeeds: Larger Models Excel in Generation, Not Discrimination
  7. 2025Logic-of-Thought: Empowering Large Language Models with Logic Programs for Solving Puzzles in Natural Language
  8. 2024Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning