mlsanityData to 7 Oct 2026

Can Large Language Models Reason and Plan?

arXiv 2403.04121 ↗First posted 7 Mar 2024cs.AI cs.CL cs.LGcited by 82

On the map: LLM reasoning → Reasoning benchmarks and evaluation

Abstract (arXiv)

While humans sometimes do show the capability of correcting their own erroneous guesses with self-critiquing, there seems to be no basis for that assumption in the case of LLMs.

Key facts. Cited by 82 papers in the map (data through 7 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 6 of its 8 references that are in the map. First posted on arXiv 7 Mar 2024.

Builds on

6 of 8 references.

References · 6

  1. 2022PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Changecited by 372
  2. 2023On the Planning Abilities of Large Language Models : A Critical Investigationcited by 308
  3. 2023Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planningcited by 204
  4. 2024LLMs Can't Plan, But Can Help Planning in LLM-Modulo Frameworkscited by 178
  5. 2023Can Large Language Models Really Improve by Self-critiquing Their Own Plans?cited by 107
  6. 2023GPT-4 Doesn't Know It's Wrong: An Analysis of Iterative Prompting for Reasoning Problemscited by 88

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 29; 2025: 39; 2026: 14.

82 papers.

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  1. 2024GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Modelscited by 533
  2. 2025LIMO: Less is More for Reasoningcited by 488
  3. 2024HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Modelscited by 273
  4. 2024To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoningcited by 257
  5. 2024LLMs Still Can't Plan; Can LRMs? A Preliminary Evaluation of OpenAI's o1 on PlanBenchcited by 93
  6. 2025PlanGenLLMs: A Modern Survey of LLM Planning Capabilitiescited by 82
  7. 2025Reasoning by Superposition: A Theoretical Perspective on Chain of Continuous Thoughtcited by 73
  8. 2024Reinforcement Learning Enhanced LLMs: A Surveycited by 69
  9. 2025Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lenscited by 42
  10. 2024Robust Planning with LLM-Modulo Framework: Case Study in Travel Planningcited by 34
  11. 2024CACTUS: Chemistry Agent Connecting Tool-Usage to Sciencecited by 32
  12. 2024LLaMAR: Long-Horizon Planning for Multi-Agent Robots in Partially Observable Environmentscited by 32
38 more
  1. 2026This human study did not involve human subjects: Validating LLM simulations as behavioral evidencecited by 26
  2. 2025PromptCoT: Synthesizing Olympiad-level Problems for Mathematical Reasoning in Large Language Modelscited by 20
  3. 2025Questioning Representational Optimism in Deep Learning: The Fractured Entangled Representation Hypothesiscited by 19
  4. 2024Quantifying Generalization Complexity for Large Language Modelscited by 18
  5. 2024TRIP-PAL: Travel Planning with Guarantees by Combining Large Language Models and Automated Plannerscited by 17
  6. 2025Post-Training Large Language Models via Reinforcement Learning from Self-Feedbackcited by 14
  7. 2024Re-TASK: Revisiting LLM Tasks from Capability, Skill, and Knowledge Perspectivescited by 13
  8. 2025Generating Symbolic World Models via Test-time Scaling of Large Language Modelscited by 12
  9. 2024Challenges in Human-Agent Communicationcited by 11
  10. 2024FLAIR: Feeding via Long-horizon AcquIsition of Realistic dishescited by 10
  11. 2024LASP: Surveying the State-of-the-Art in Large Language Model-Assisted AI Planningcited by 9
  12. 2024Open-World Task and Motion Planning via Vision-Language Model Generated Constraintscited by 9
  13. 2024Language Agents Meet Causality -- Bridging LLMs and Causal World Modelscited by 8
  14. 2026Causality is Key for Interpretability Claims to Generalisecited by 8
  15. 2024Towards a Benchmark for Causal Business Process Reasoning with LLMscited by 7
  16. 2025FEAST: A Flexible Mealtime-Assistance System Towards In-the-Wild Personalizationcited by 7
  17. 2025Procedural Knowledge Improves Agentic LLM Workflowscited by 7
  18. 2024Frontier AI Ethics: Anticipating and Evaluating the Societal Impacts of Language Model Agentscited by 5
  19. 2024Large corpora and large language models: a replicable method for automating grammatical annotationcited by 5
  20. 2025A Knapsack by Any Other Name: Presentation impacts LLM performance on NP-hard problemscited by 5
  21. 2025Haste Makes Waste: Evaluating Planning Abilities of LLMs for Efficient and Feasible Multitasking with Time Constraints Between Actionscited by 5
  22. 2025LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integrationcited by 5
  23. 2025The Need for Verification in AI-Driven Scientific Discoverycited by 5
  24. 2024Harnessing the Power of Semi-Structured Knowledge and LLMs with Triplet-Based Prefiltering for Question Answeringcited by 4
  25. 2025The Hitchhiker's Guide to Program Analysis, Part II: Deep Thoughts by LLMscited by 4
  26. 2025Towards Reliable LLM-based Robot Planning via Combined Uncertainty Estimationcited by 4
  27. 2025Fetch.ai: An Architecture for Modern Multi-Agent Systemscited by 4
  28. 2026Agentic Design Patterns: A System-Theoretic Frameworkcited by 4
  29. 2025LINGOLY-TOO: Disentangling Reasoning from Knowledge with Templatised Orthographic Obfuscationcited by 3
  30. 2025Cross-Lingual Prompt Steerability: Towards Accurate and Robust LLM Behavior across Languagescited by 3
  31. 2024Over the Edge of Chaos? Excess Complexity as a Roadblock to Artificial General Intelligencecited by 2
  32. 2024Iterative Graph Alignmentcited by 2
  33. 2024Image First or Text First? Optimising the Sequencing of Modalities in Large Language Model Prompting and Reasoning Taskscited by 2
  34. 2024Can LLMs plan paths in the real world?cited by 2
  35. 2025Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledgecited by 2
  36. 2025Semantic Communication meets System 2 ML: How Abstraction, Compositionality and Emergent Languages Shape Intelligencecited by 2
  37. 2025Vision-Language Models Mistake Head Orientation for Gaze Direction: Nonverbal Conversation Cuescited by 2
  38. 2025KisMATH: Do LLMs Have Knowledge of Implicit Structures in Mathematical Reasoning?cited by 2

50 most cited of 82 All 82 (JSON)

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  1. 2025LLMs Don't Know Their Own Decision Boundaries: The Unreliability of Self-Generated Counterfactual Explanations
  2. 2025Why Cannot Large Language Models Ever Make True Correct Reasoning?
  3. 2026Do LLM Self-Explanations Help Users Predict Model Behavior? Evaluating Counterfactual Simulatability with Pragmatic Perturbations
  4. 2025Position: On the Methodological Pitfalls of Evaluating Base LLMs for Reasoning
  5. 2024Take Caution in Using LLMs as Human Surrogates: Scylla Ex Machina
  6. 2024Easy Problems That LLMs Get Wrong
  7. 2024Will the Real Linda Please Stand up...to Large Language Models? Examining the Representativeness Heuristic in LLMs
  8. 2025Large Language Models are overconfident and amplify human bias