mlsanityData to 7 Oct 2026

A Survey on Large Language Model Hallucination via a Creativity Perspective

arXiv 2402.06647 ↗First posted 2 Feb 2024cs.AI cs.HCcited by 38

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Abstract (arXiv)

Hallucinations in large language models (LLMs) are always seen as limitations. However, could they also be a source of creativity? This survey explores this possibility, suggesting that hallucinations may contribute to LLM application by fostering creativity. This survey begins with a review of the taxonomy of hallucinations and their negative impact on LLM reliability in critical applications. Then, through historical examples and recent relevant theories, the survey explores the potential creative benefits of hallucinations in LLMs. To elucidate the value and evaluation criteria of this connection, we delve into the definitions and assessment methods of creativity. Following the framework of divergent and convergent thinking phases, the survey systematically reviews the literature on transforming and harnessing hallucinations for creativity in LLMs. Finally, the survey discusses future research directions, emphasizing the need to further explore and refine the application of hallucinations in creative processes within LLMs.

Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). Builds on 20 of its 53 references that are in the map. First posted on arXiv 2 Feb 2024.

Builds on

20 of 53 references.

References · 20

  1. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  2. 2021TruthfulQA: Measuring How Models Mimic Human Falsehoodscited by 2,919
  3. 2022Survey of Hallucination in Natural Language Generationcited by 2,056
  4. 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,582
  5. 2023Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debatecited by 995
  6. 2023Large Language Modelscited by 774
  7. 2023ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debatecited by 724
  8. 2023Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Modelscited by 695
  9. 2023A Survey of Hallucination in Large Foundation Modelscited by 365
  10. 2023HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Modelscited by 329
  11. 2024A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Modelscited by 266
  12. 2023Med-HALT: Medical Domain Hallucination Test for Large Language Modelscited by 156
8 more
  1. 2021Neural Path Hunter: Reducing Hallucination in Dialogue Systems via Path Groundingcited by 106
  2. 2023Can Knowledge Graphs Reduce Hallucinations in LLMs? : A Surveycited by 92
  3. 2023Cognitive Mirage: A Review of Hallucinations in Large Language Modelscited by 83
  4. 2022Putting GPT-3's Creativity to the (Alternative Uses) Testcited by 62
  5. 2024Assessing and Understanding Creativity in Large Language Modelscited by 35
  6. 2023Creative Agents: Empowering Agents with Imagination for Creative Taskscited by 24
  7. 2023User-Controlled Knowledge Fusion in Large Language Models: Balancing Creativity and Hallucinationcited by 7
  8. 2024LightHouse: A Survey of AGI Hallucinationcited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 9; 2025: 25; 2026: 4.

38 papers.

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  1. 2024A Survey on the Memory Mechanism of Large Language Model based Agentscited by 622
  2. 2025Are Reasoning Models More Prone to Hallucination?cited by 62
  3. 2024Large Language Models Assume People are More Rational than We Really arecited by 49
  4. 2025Large Language Models Hallucination: A Comprehensive Surveycited by 45
  5. 2025Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoningcited by 33
  6. 2025Lost in Transcription, Found in Distribution Shift: Demystifying Hallucination in Speech Foundation Modelscited by 17
  7. 2024Interpreting and Mitigating Hallucination in MLLMs through Multi-agent Debatecited by 16
  8. 2024Real or Robotic? Assessing Whether LLMs Accurately Simulate Qualities of Human Responses in Dialoguecited by 15
  9. 2024Fakes of Varying Shades: How Warning Affects Human Perception and Engagement Regarding LLM Hallucinationscited by 12
  10. 2026CreativeBench: Benchmarking and Enhancing Machine Creativity via Self-Evolving Challengescited by 9
  11. 2024AutoTRIZ: Automating Engineering Innovation with TRIZ and Large Language Modelscited by 8
  12. 2025DioR: Adaptive Cognitive Detection and Contextual Retrieval Optimization for Dynamic Retrieval-Augmented Generationcited by 7
26 more
  1. 2025Loki's Dance of Illusions: A Comprehensive Survey of Hallucination in Large Language Modelscited by 6
  2. 2025Preventing Rogue Agents Improves Multi-Agent Collaborationcited by 3
  3. 2025Shakespearean Sparks: The Dance of Hallucination and Creativity in LLMs' Decoding Layerscited by 3
  4. 2025Cooking Up Creativity: Enhancing LLM Creativity through Structured Recombinationcited by 3
  5. 2025From Context to EDUs: Faithful and Structured Context Compression via Elementary Discourse Unit Decompositioncited by 3
  6. 2024LLM2TEA: An Agentic AI Designer for Discovery with Generative Evolutionary Multitaskingcited by 2
  7. 2025Can Hallucinations Help? Boosting LLMs for Drug Discoverycited by 2
  8. 2025TPU-Gen: LLM-Driven Custom Tensor Processing Unit Generatorcited by 2
  9. 2025MultiHal: Multilingual Dataset for Knowledge-Graph Grounded Evaluation of LLM Hallucinationscited by 2
  10. 2025Adversarial Activation Patching: A Framework for Detecting and Mitigating Emergent Deception in Safety-Aligned Transformerscited by 2
  11. 2025Mitigating Hallucination in Large Language Models (LLMs): An Application-Oriented Survey on RAG, Reasoning, and Agentic Systemscited by 2
  12. 2025Critical Confabulation: Can LLMs Hallucinate for Social Good?cited by 2
  13. 2025Heaven-Sent or Hell-Bent? Benchmarking the Intelligence and Defectiveness of LLM Hallucinationscited by 2
  14. 2024LLM4DESIGN: An Automated Multi-Modal System for Architectural and Environmental Designcited by 1
  15. 2025Library Hallucinations in LLM-Generated Code: A Risk Analysis Grounded in Developer Queriescited by 1
  16. 2026Harmless Yet Harmful: Neutral Prompting Attacks for Stealthy Hallucination Steering in Agent Skillscited by 1
  17. 2024FiSTECH: Financial Style Transfer to Enhance Creativity without Hallucinations in LLMscited by 0
  18. 2025MIH-TCCT: Mitigating Inconsistent Hallucinations in LLMs via Event-Driven Text-Code Cyclic Trainingcited by 0
  19. 2025Evaluation and Incident Prevention in an Enterprise AI Assistantcited by 0
  20. 2025Conservative Bias in Large Language Models: Measuring Relation Predictionscited by 0
  21. 2025Are Hallucinations Bad Estimations?cited by 0
  22. 2025Enhancing Faithfulness in Abstractive Summarization via Span-Level Fine-Tuningcited by 0
  23. 2025FlexAC: Towards Flexible Control of Associative Reasoning in Multimodal Large Language Modelscited by 0
  24. 2025MazeMate: An LLM-Powered Chatbot to Support Computational Thinking in Gamified Programming Learningcited by 0
  25. 2026Hallucination-aware intermediate representation edit in large vision-language modelscited by 0
  26. 2026How Well Can AI Generate Backlogs from App Mockups?cited by 0