mlsanityData to 14 Oct 2026

Aspects of human memory and Large Language Models

arXiv 2311.03839 ↗First posted 7 Nov 2023cs.CL cs.AI cs.LGcited by 12

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Abstract (arXiv)

Large Language Models (LLMs) are huge artificial neural networks which primarily serve to generate text, but also provide a very sophisticated probabilistic model of language use. Since generating a semantically consistent text requires a form of effective memory, we investigate the memory properties of LLMs and find surprising similarities with key characteristics of human memory. We argue that the human-like memory properties of the Large Language Model do not follow automatically from the LLM architecture but are rather learned from the statistics of the training textual data. These results strongly suggest that the biological features of human memory leave an imprint on the way that we structure our textual narratives.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 11 of its 23 references that are in the map. First posted on arXiv 7 Nov 2023.

Builds on

11 of 23 references.

References · 11

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2022Training language models to follow instructions with human feedbackcited by 15,971
  4. 2021RoFormer: Enhanced Transformer with Rotary Position Embeddingcited by 4,703
  5. 2017Deep reinforcement learning from human preferencescited by 3,912
  6. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,592
  7. 2020The Pile: An 800GB Dataset of Diverse Text for Language Modelingcited by 2,411
  8. 2023Pythia: A Suite for Analyzing Large Language Models Across Training and Scalingcited by 1,786
  9. 2022Using cognitive psychology to understand GPT-3cited by 398
  10. 2023Art or Artifice? Large Language Models and the False Promise of Creativitycited by 172
  11. 2023Cognitive Effects in Large Language Modelscited by 14

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Cited by year

Citing papers per year: 2024: 6; 2025: 6.

12 papers.

  1. 2025A Survey of Context Engineering for Large Language Modelscited by 126
  2. 2024AriGraph: Learning Knowledge Graph World Models with Episodic Memory for LLM Agentscited by 102
  3. 2024Attention Heads of Large Language Models: A Surveycited by 67
  4. 2024Large Language Models and Cognitive Science: A Comprehensive Review of Similarities, Differences, and Challengescited by 49
  5. 2025Mixing Mechanisms: How Language Models Retrieve Bound Entities In-Contextcited by 26
  6. 2024Human-like object concept representations emerge naturally in multimodal large language modelscited by 25
  7. 2024Large Language Model Benchmarks in Medical Taskscited by 17
  8. 2025IMPersona: Evaluating Individual Level LM Impersonationcited by 11
  9. 2025Lost in the Middle: An Emergent Property from Information Retrieval Demands in LLMscited by 9
  10. 2024Relative Value Biases in Large Language Modelscited by 6
  11. 2025Emergence of the Primacy Effect in Structured State-Space Modelscited by 4
  12. 2025Memorization and Knowledge Injection in Gated LLMscited by 3