Does It Make Sense to Speak of Introspection in Large Language Models?
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Abstract (arXiv)
Large language models (LLMs) exhibit compelling linguistic behaviour, and sometimes offer self-reports, that is to say statements about their own nature, inner workings, or behaviour. In humans, such reports are often attributed to a faculty of introspection and are typically linked to consciousness. This raises the question of how to interpret self-reports produced by LLMs, given their increasing linguistic fluency and cognitive capabilities. To what extent (if any) can the concept of introspection be meaningfully applied to LLMs? Here, we present and critique two examples of apparent introspective self-report from LLMs. In the first example, an LLM attempts to describe the process behind its own "creative" writing, and we argue this is not a valid example of introspection. In the second example, an LLM correctly infers the value of its own temperature parameter, and we argue that this can be legitimately considered a minimal example of introspection, albeit one that is (presumably) not accompanied by conscious experience.
Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). Builds on 20 of its 51 references that are in the map. First posted on arXiv 5 Jun 2025.
Builds on
20 of 51 references.
References · 20
- 2022Emergent Abilities of Large Language Modelscited by 2,483
- 2022Language Models (Mostly) Know What They Knowcited by 1,783
- 2024LLM Evaluators Recognize and Favor Their Own Generationscited by 651
- 2023Role-Play with Large Language Modelscited by 290
- 2023Do Large Language Models Know What They Don't Know?cited by 238
- 2023FANToM: A Benchmark for Stress-testing Machine Theory of Mind in Interactionscited by 162
- 2024Looking Inward: Language Models Can Learn About Themselves by Introspectioncited by 105
- 2023Consciousness in Artificial Intelligence: Insights from the Science of Consciousnesscited by 99
- 2024Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solvingcited by 82
- 2024Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMscited by 78
- 2023Self-Evaluation Improves Selective Generation in Large Language Modelscited by 74
- 2023Could a Large Language Model be Conscious?cited by 70
8 more
- 2023Two Failures of Self-Consistency in the Multi-Step Reasoning of LLMscited by 36
- 2023Towards Evaluating AI Systems for Moral Status Using Self-Reportscited by 21
- 2023The feasibility of artificial consciousness through the lens of neurosciencecited by 18
- 2024Self-Recognition in Language Modelscited by 17
- 2024Simulacra as Conscious Exoticacited by 16
- 2024From Imitation to Introspection: Probing Self-Consciousness in Language Modelscited by 14
- 2020Intrinsic Robotic Introspection: Learning Internal States From Neuron Activationscited by 1
- 2023Introspective Perception for Mobile Robotscited by 1
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Citing papers per year: 2025: 6; 2026: 16.
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- 2025Training Language Models to Explain Their Own Computationscited by 27
- 2025Privileged Self-Access Matters for Introspection in AIcited by 20
- 2026Counterfactual Simulation Training for Chain-of-Thought Faithfulnesscited by 15
- 2025A validity-guided workflow for robust large language model research in psychologycited by 8
- 2025Know Thyself? On the Incapability and Implications of AI Self-Recognitioncited by 7
- 2025Generalized Correctness Models: Learning Calibrated and Model-Agnostic Correctness Predictors from Historical Patternscited by 5
- 2026Emergent Introspection in AI is Content-Agnosticcited by 5
- 2026Language models recognize dropout and Gaussian noise applied to their activationscited by 3
- 2026Introspective Coupling: Self-Explanation Training Tracks Behavioral Change Despite Fixed Supervisioncited by 3
- 2026Fine-Tuning Language Models to Know What They Knowcited by 2
- 2026Self-Reference in Large Language Models: The Introspection Threshold for Recursive Self-Improvementcited by 2
- 2025Minimal and Mechanistic Conditions for Behavioral Self-Awareness in LLMscited by 1
10 more
- 2026Quantitative Introspection in Language Models: Tracking Emotive States Across Conversationcited by 1
- 2026On the Creativity of AI Agentscited by 1
- 2026AI and Consciousness: Shifting Focus Towards Tractable Questionscited by 1
- 2026Beyond Confidence: Rethinking Self-Assessments for Performance Prediction in LLMscited by 1
- 2026Metacognition in LLMs: Foundations, Progress, and Opportunitiescited by 1
- 2026LLM Self-Explanations Fail Semantic Invariancecited by 0
- 2026The Pinocchio Dimension: Phenomenality of Experience as the Primary Axis of LLM Psychometric Differencescited by 0
- 2026Asymmetric Communication: Large Language Models and Language Gamescited by 0
- 2026Self-Referential Induction Increases Response Instability Relative to Unresolvable and Verifiable Questions in Large Language Modelscited by 0
- 2026"As a Language Model...": Chat Template Switches LLM Self-Referential Voice and Activation Steering Reproduces Itcited by 0
- 2026Self-Referential Induction Increases Response Instability Relative to Unresolvable and Verifiable Questions in Large Language Models13 Aug 2026
- 2026"As a Language Model...": Chat Template Switches LLM Self-Referential Voice and Activation Steering Reproduces It9 Aug 2026
- 2026Asymmetric Communication: Large Language Models and Language Games30 Jul 2026
- 2026Metacognition in LLMs: Foundations, Progress, and Opportunities13 Jul 2026
- 2026Self-Reference in Large Language Models: The Introspection Threshold for Recursive Self-Improvement5 Jul 2026
- 2026Introspective Coupling: Self-Explanation Training Tracks Behavioral Change Despite Fixed Supervision30 Jun 2026
- 2026Beyond Confidence: Rethinking Self-Assessments for Performance Prediction in LLMs8 May 2026
- 2026AI and Consciousness: Shifting Focus Towards Tractable Questions7 May 2026
- 2026The Pinocchio Dimension: Phenomenality of Experience as the Primary Axis of LLM Psychometric Differences6 May 2026
- 2026Language models recognize dropout and Gaussian noise applied to their activations19 Apr 2026
- 2026On the Creativity of AI Agents14 Apr 2026
- 2026Quantitative Introspection in Language Models: Tracking Emotive States Across Conversation19 Mar 2026
10 more
- 2026Emergent Introspection in AI is Content-Agnostic5 Mar 2026
- 2026LLM Self-Explanations Fail Semantic Invariance1 Mar 2026
- 2026Counterfactual Simulation Training for Chain-of-Thought Faithfulness24 Feb 2026
- 2026Fine-Tuning Language Models to Know What They Know2 Feb 2026
- 2025Training Language Models to Explain Their Own Computations11 Nov 2025
- 2025Minimal and Mechanistic Conditions for Behavioral Self-Awareness in LLMs6 Nov 2025
- 2025Know Thyself? On the Incapability and Implications of AI Self-Recognition3 Oct 2025
- 2025Generalized Correctness Models: Learning Calibrated and Model-Agnostic Correctness Predictors from Historical Patterns29 Sep 2025
- 2025Privileged Self-Access Matters for Introspection in AI20 Aug 2025
- 2025A validity-guided workflow for robust large language model research in psychology6 Jul 2025
- 2026On the Creativity of AI Agentscited by 1
- 2026On the Creativity of AI Agents14 Apr 2026
- 2025Training Language Models to Explain Their Own Computationscited by 27
- 2025Privileged Self-Access Matters for Introspection in AIcited by 20
- 2025A validity-guided workflow for robust large language model research in psychologycited by 8
- 2025Know Thyself? On the Incapability and Implications of AI Self-Recognitioncited by 7
- 2025Generalized Correctness Models: Learning Calibrated and Model-Agnostic Correctness Predictors from Historical Patternscited by 5
- 2026Emergent Introspection in AI is Content-Agnosticcited by 5
- 2026Language models recognize dropout and Gaussian noise applied to their activationscited by 3
- 2026Introspective Coupling: Self-Explanation Training Tracks Behavioral Change Despite Fixed Supervisioncited by 3
- 2026Fine-Tuning Language Models to Know What They Knowcited by 2
- 2025Minimal and Mechanistic Conditions for Behavioral Self-Awareness in LLMscited by 1
- 2026Quantitative Introspection in Language Models: Tracking Emotive States Across Conversationcited by 1
- 2026AI and Consciousness: Shifting Focus Towards Tractable Questionscited by 1
12 most cited of 18 All 18 (JSON)
- 2026Self-Referential Induction Increases Response Instability Relative to Unresolvable and Verifiable Questions in Large Language Models13 Aug 2026
- 2026"As a Language Model...": Chat Template Switches LLM Self-Referential Voice and Activation Steering Reproduces It9 Aug 2026
- 2026Asymmetric Communication: Large Language Models and Language Games30 Jul 2026
- 2026Metacognition in LLMs: Foundations, Progress, and Opportunities13 Jul 2026
- 2026Introspective Coupling: Self-Explanation Training Tracks Behavioral Change Despite Fixed Supervision30 Jun 2026
- 2026AI and Consciousness: Shifting Focus Towards Tractable Questions7 May 2026
- 2026The Pinocchio Dimension: Phenomenality of Experience as the Primary Axis of LLM Psychometric Differences6 May 2026
- 2026Language models recognize dropout and Gaussian noise applied to their activations19 Apr 2026
- 2026Quantitative Introspection in Language Models: Tracking Emotive States Across Conversation19 Mar 2026
- 2026Emergent Introspection in AI is Content-Agnostic5 Mar 2026
- 2026LLM Self-Explanations Fail Semantic Invariance1 Mar 2026
- 2026Fine-Tuning Language Models to Know What They Know2 Feb 2026
12 newest of 18 All 18 (JSON)