mlsanityData to 14 Oct 2026

How LLMs Might Think

arXiv 2604.09674 ↗First posted 2 Apr 2026cs.AI cs.CLcited by 0

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Abstract (arXiv)

Do large language models (LLMs) think? Daniel Stoljar and Zhihe Vincent Zhang have recently developed an argument from rationality for the claim that LLMs do not think. We contend, however, that the argument from rationality not only falters, but leaves open an intriguing possibility: that LLMs engage only in arational, associative forms of thinking, and have purely associative minds. Our positive claim is that if LLMs think at all, they likely think precisely in this manner.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 17 of its 57 references that are in the map. First posted on arXiv 2 Apr 2026.

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17 of 57 references.

References · 17

  1. 2017Attention Is All You Needcited by 60,361
  2. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,592
  3. 2021Probing Classifiers: Promises, Shortcomings, and Advancescited by 876
  4. 2022A Survey on In-context Learningcited by 721
  5. 2022What learning algorithm is in-context learning? Investigations with linear modelscited by 684
  6. 2022Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Taskcited by 431
  7. 2017Structured Attention Networkscited by 95
  8. 2024Reuse, Don't Retrain: A Recipe for Continued Pretraining of Language Modelscited by 72
  9. 2023From task structures to world models: What do LLMs know?cited by 46
  10. 2024Standards for Belief Representations in LLMscited by 30
  11. 2024A Philosophical Introduction to Language Models -- Part I: Continuity With Classic Debatescited by 23
  12. 2024Model Surgery: Modulating LLM's Behavior Via Simple Parameter Editingcited by 23
5 more
  1. 2024Does ChatGPT Have a Mind?cited by 14
  2. 2025Propositional Interpretability in Artificial Intelligencecited by 12
  3. 2024Optimizing Large Language Model Hyperparameters for Code Generationcited by 11
  4. 2024Real Sparks of Artificial Intelligence and the Importance of Inner Interpretabilitycited by 4
  5. 2022Do Transformers know symbolic rules, and would we know if they did?cited by 1

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  1. 2025Why LLMs Cannot Think and How to Fix It
  2. 2025What Kind of Reasoning (if any) is an LLM actually doing? On the Stochastic Nature and Abductive Appearance of Large Language Models
  3. 2025Language and Thought: The View from LLMs
  4. 2024(Ir)rationality and Cognitive Biases in Large Language Models
  5. 2025Do LLMs Really Need 10+ Thoughts for "Find the Time 1000 Days Later"? Towards Structural Understanding of LLM Overthinking
  6. 2024Do Large Language Models Truly Grasp Mathematics? An Empirical Exploration From Cognitive Psychology
  7. 2024Can Large Language Models Reason and Plan?
  8. 2023Are LLMs the Master of All Trades? : Exploring Domain-Agnostic Reasoning Skills of LLMs