mlsanityData to 14 Oct 2026

Towards Better Chain-of-Thought Prompting Strategies: A Survey

arXiv 2310.04959 ↗First posted 8 Oct 2023cs.CLcited by 62

On the map: LLM reasoning → Prompting and chain-of-thought reasoning

Abstract (arXiv)

Chain-of-Thought (CoT), a step-wise and coherent reasoning chain, shows its impressive strength when used as a prompting strategy for large language models (LLM). Recent years, the prominent effect of CoT prompting has attracted emerging research. However, there still lacks of a systematic summary about key factors of CoT prompting and comprehensive guide for prompts utilizing. For a deeper understanding about CoT prompting, we survey on a wide range of current research, presenting a systematic and comprehensive analysis on several factors that may influence the effect of CoT prompting, and introduce how to better apply it in different applications under these discussions. We further analyze the challenges and propose some future directions about CoT prompting. This survey could provide an overall reference on related research.

Key facts. Cited by 62 papers in the map (data through 14 Oct 2026). Placed in Prompting and chain-of-thought reasoning, one of 17 directions in LLM reasoning. Builds on 94 of its 113 references that are in the map. First posted on arXiv 8 Oct 2023.

Builds on

94 of 113 references.

Closest ancestors · 23

Same direction, newest first

  1. 2023Dissecting Chain-of-Thought: Compositionality through In-Context Filtering and Learning30 May
  2. 2023Progressive-Hint Prompting Improves Reasoning in Large Language Models19 Apr
  3. 2023Why think step by step? Reasoning emerges from the locality of experience7 Apr
  4. 2023CoTEVer: Chain of Thought Prompting Annotation Toolkit for Explanation Verification7 Mar
  5. 2023Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data24 Feb
  6. 2023Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models1 Feb
  7. 2023Faithful Chain-of-Thought Reasoning31 Jan
  8. 2023ThoughtSource: A central hub for large language model reasoning data27 Jan
  9. 2022Large Language Models Are Reasoning Teachers20 Dec
  10. 2022Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters20 Dec
  11. 2022Reasoning with Language Model Prompting: A Survey19 Dec
  12. 2022Teaching Small Language Models to Reason16 Dec
11 more
  1. 2022Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks22 Nov
  2. 2022Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them17 Oct
  3. 2022Automatic Chain of Thought Prompting in Large Language Models7 Oct
  4. 2022Complexity-Based Prompting for Multi-Step Reasoning3 Oct
  5. 2022Text and Patterns: For Effective Chain of Thought, It Takes Two to Tango16 Sep
  6. 2022Large Language Models are Zero-Shot Reasoners24 May
  7. 2022Maieutic Prompting: Logically Consistent Reasoning with Recursive Explanations24 May
  8. 2022Least-to-Most Prompting Enables Complex Reasoning in Large Language Models21 May
  9. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Models21 Mar
  10. 2022Iteratively Prompt Pre-trained Language Models for Chain of Thought16 Mar
  11. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Models28 Jan

Other references · 71

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2022Training language models to follow instructions with human feedbackcited by 15,971
  3. 2021Training Verifiers to Solve Math Word Problemscited by 10,109
  4. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,326
  5. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
  6. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 3,050
  7. 2022Scaling Instruction-Finetuned Language Modelscited by 3,024
  8. 2023A Survey of Large Language Modelscited by 2,576
  9. 2022Survey of Hallucination in Natural Language Generationcited by 2,075
  10. 2022Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answeringcited by 1,919
  11. 2022Large Language Models Encode Clinical Knowledgecited by 1,830
  12. 2021Multitask Prompted Training Enables Zero-Shot Task Generalizationcited by 1,470
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  1. 2021What Makes Good In-Context Examples for GPT-3?cited by 1,195
  2. 2023HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Facecited by 1,190
  3. 2021Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivitycited by 1,135
  4. 2022Measuring and Narrowing the Compositionality Gap in Language Modelscited by 1,075
  5. 2022Large Language Models Are Human-Level Prompt Engineerscited by 1,045
  6. 2022In-context Learning and Induction Headscited by 964
  7. 2022STaR: Bootstrapping Reasoning With Reasoningcited by 940
  8. 2021An Explanation of In-context Learning as Implicit Bayesian Inferencecited by 938
  9. 2022Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questionscited by 923
  10. 2023Multimodal Chain-of-Thought Reasoning in Language Modelscited by 752
  11. 2022A Survey on In-context Learningcited by 721
  12. 2022What Can Transformers Learn In-Context? A Case Study of Simple Function Classescited by 715
  13. 2020It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learnerscited by 669
  14. 2022Large Language Models Can Self-Improvecited by 664
  15. 2022PAL: Program-aided Language Modelscited by 652
  16. 2022Towards Reasoning in Large Language Models: A Surveycited by 596
  17. 2022Decomposed Prompting: A Modular Approach for Solving Complex Taskscited by 558
  18. 2022Language Models are Multilingual Chain-of-Thought Reasonerscited by 530
  19. 2023DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correctioncited by 477
  20. 2019Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methodscited by 443
  21. 2022PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Changecited by 382
  22. 2023Chameleon: Plug-and-Play Compositional Reasoning with Large Language Modelscited by 356
  23. 2022Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thoughtcited by 337
  24. 2022Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoningcited by 334
  25. 2022Data Distributional Properties Drive Emergent In-Context Learning in Transformerscited by 309
  26. 2022Black-Box Tuning for Language-Model-as-a-Servicecited by 256
  27. 2023Specializing Smaller Language Models towards Multi-Step Reasoningcited by 251
  28. 2023MathPrompter: Mathematical Reasoning using Large Language Modelscited by 236
  29. 2023Transformers as Algorithms: Generalization and Stability in In-context Learningcited by 222
  30. 2022Exploring Length Generalization in Large Language Modelscited by 206
  31. 2022Why Can GPT Learn In-Context? Language Models Implicitly Perform Gradient Descent as Meta-Optimizerscited by 204
  32. 2023Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoningcited by 178
  33. 2022The Unreliability of Explanations in Few-shot Prompting for Textual Reasoningcited by 169
  34. 2018Measuring abstract reasoning in neural networkscited by 166
  35. 2021Template-Based Named Entity Recognition Using BARTcited by 153
  36. 2022Rethinking with Retrieval: Faithful Large Language Model Inferencecited by 145
  37. 2023Self-planning Code Generation with Large Language Modelscited by 124
  38. 2022Large Language Models are few(1)-shot Table Reasonerscited by 116

50 most cited of 71 All 71 (JSON)

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Citing papers per year: 2023: 3; 2024: 20; 2025: 26; 2026: 13.

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  1. 2024FineSurE: Fine-grained Summarization Evaluation using LLMscited by 83
  2. 2023Igniting Language Intelligence: The Hitchhiker's Guide From Chain-of-Thought Reasoning to Language Agentscited by 72
  3. 2024Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMscited by 48
  4. 2024Puzzle Solving using Reasoning of Large Language Models: A Surveycited by 45
  5. 2025Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lenscited by 43
  6. 2024RATT: A Thought Structure for Coherent and Correct LLM Reasoningcited by 41
  7. 2024Prompting Techniques for Reducing Social Bias in LLMs through System 1 and System 2 Cognitive Processescited by 39
  8. 2025Navigate the Unknown: Enhancing LLM Reasoning with Intrinsic Motivation Guided Explorationcited by 34
  9. 2024Cycles of Thought: Measuring LLM Confidence through Stable Explanationscited by 29
  10. 2025PixelThink: Towards Efficient Chain-of-Pixel Reasoningcited by 28
  11. 2024Dynamic and Adaptive Feature Generation with LLMcited by 27
  12. 2024Pirates of the RAG: Adaptively Attacking LLMs to Leak Knowledge Basescited by 18
38 more
  1. 2024Do LLMs Really Think Step-by-step In Implicit Reasoning?cited by 16
  2. 2025CoTMR: Chain-of-Thought Multi-Scale Reasoning for Training-Free Zero-Shot Composed Image Retrievalcited by 16
  3. 2025Simulating Society Requires Simulating Thoughtcited by 13
  4. 2024Efficient Prompting for LLM-based Generative Internet of Thingscited by 12
  5. 2024OCEAN: Offline Chain-of-thought Evaluation and Alignment in Large Language Modelscited by 12
  6. 2025Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospectscited by 12
  7. 2025Privacy-Aware RAG: Secure and Isolated Knowledge Retrievalcited by 10
  8. 2024An Empirical Categorization of Prompting Techniques for Large Language Models: A Practitioner's Guidecited by 7
  9. 2024TransAgent: Enhancing LLM-Based Code Translation via Fine-Grained Execution Alignmentcited by 7
  10. 2025Approximating Human Strategic Reasoning with LLM-Enhanced Recursive Reasoners Leveraging Multi-agent Hypergamescited by 7
  11. 2023Beyond Isolation: Multi-Agent Synergy for Improving Knowledge Graph Constructioncited by 6
  12. 2025An LLM Agentic Approach for Legal-Critical Software: A Case Study for Tax Prep Softwarecited by 6
  13. 2025Benchmarking LLM-Assisted Blue Teaming via Standardized Threat Huntingcited by 6
  14. 2024Aggregation of Reasoning: A Hierarchical Framework for Enhancing Answer Selection in Large Language Modelscited by 5
  15. 2025LingBench++: A Linguistically-Informed Benchmark and Reasoning Framework for Multi-Step and Cross-Cultural Inference with LLMscited by 5
  16. 2025CoDAE: Adapting Large Language Models for Education via Chain-of-Thought Data Augmentationcited by 5
  17. 2024"Let's Argue Both Sides": Argument Generation Can Force Small Models to Utilize Previously Inaccessible Reasoning Capabilitiescited by 4
  18. 2025Graph-Grounded LLMs: Leveraging Graphical Function Calling to Minimize LLM Hallucinationscited by 4
  19. 2025LOGicalThought: Logic-Based Ontological Grounding of LLMs for High-Assurance Reasoningcited by 4
  20. 2026Are LLMs Reliable Code Reviewers? Systematic Overcorrection in Requirement Conformance Judgementcited by 4
  21. 2026Learning from Your Own Mistakes: Constructing Learnable Micro-Reflective Trajectories for Self-Distillationcited by 4
  22. 2024Towards Goal-oriented Prompt Engineering for Large Language Models: A Surveycited by 3
  23. 2024Image First or Text First? Optimising the Sequencing of Modalities in Large Language Model Prompting and Reasoning Taskscited by 3
  24. 2025Fully Autonomous Programming using Iterative Multi-Agent Debugging with Large Language Modelscited by 3
  25. 2025Meeseeks: A Feedback-Driven, Iterative Self-Correction Benchmark evaluating LLMs' Instruction Following Capabilitycited by 3
  26. 2026TDA-RC: Task-Driven Alignment for Knowledge-Based Reasoning Chains in Large Language Modelscited by 3
  27. 2023The Tyranny of Possibilities in the Design of Task-Oriented LLM Systems: A Scoping Surveycited by 2
  28. 2025Kongzi: A Historical Large Language Model with Fact Enhancementcited by 2
  29. 2025Synthetic Heuristic Evaluation: A Comparison between AI- and Human-Powered Usability Evaluationcited by 2
  30. 2024Evaluating ChatGPT-3.5 Efficiency in Solving Coding Problems of Different Complexity Levels: An Empirical Analysiscited by 1
  31. 2025Detecting and Mitigating DDoS Attacks with AI: A Surveycited by 1
  32. 2025On the Limits of Innate Planning in Large Language Modelscited by 1
  33. 2025Understanding Chain-of-Thought in Large Language Models via Topological Data Analysiscited by 1
  34. 2026Inference-Time Scaling for Visual AutoRegressive modeling by Searching Representative Samplescited by 1
  35. 2026Intelligent Documentation in Medical Education: Can AI Replace Manual Case Logging?cited by 1
  36. 2024GuReT: Distinguishing Guilt and Regret related Textcited by 0
  37. 2024Patience Is The Key to Large Language Model Reasoningcited by 0
  38. 2025Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Modelscited by 0

50 most cited of 62 All 62 (JSON)

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  1. 2025Prompting Science Report 2: The Decreasing Value of Chain of Thought in Prompting
  2. 2024Enhancing Chain of Thought Prompting in Large Language Models via Reasoning Patterns
  3. 2023Chain-Of-Thought Prompting Under Streaming Batch: A Case Study
  4. 2023Stress Testing Chain-of-Thought Prompting for Large Language Models
  5. 2024Unveiling the Statistical Foundations of Chain-of-Thought Prompting Methods
  6. 2024Towards Better Chain-of-Thought: A Reflection on Effectiveness and Faithfulness
  7. 2024Can Separators Improve Chain-of-Thought Prompting?
  8. 2024ChainLM: Empowering Large Language Models with Improved Chain-of-Thought Prompting