mlsanityData to 7 Oct 2026

Large Language Model Recall Uncertainty is Modulated by the Fan Effect

arXiv 2407.06349 ↗First posted 8 Jul 2024cs.CL cs.AIcited by 7

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Abstract (arXiv)

This paper evaluates whether large language models (LLMs) exhibit cognitive fan effects, similar to those discovered by Anderson in humans, after being pre-trained on human textual data. We conduct two sets of in-context recall experiments designed to elicit fan effects. Consistent with human results, we find that LLM recall uncertainty, measured via token probability, is influenced by the fan effect. Our results show that removing uncertainty disrupts the observed effect. The experiments suggest the fan effect is consistent whether the fan value is induced in-context or in the pre-training data. Finally, these findings provide in-silico evidence that fan effects and typicality are expressions of the same phenomena.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 22 of its 42 references that are in the map. First posted on arXiv 8 Jul 2024.

Builds on

22 of 42 references.

References · 22

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10 more
  1. 2022minicons: Enabling Flexible Behavioral and Representational Analyses of Transformer Language Modelscited by 58
  2. 2021Structural Persistence in Language Models: Priming as a Window into Abstract Language Representationscited by 44
  3. 2023Do Large Language Models Show Decision Heuristics Similar to Humans? A Case Study Using GPT-3.5cited by 41
  4. 2021Do language models learn typicality judgments from text?cited by 32
  5. 2023How Powerful are Decoder-Only Transformer Neural Models?cited by 20
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 4; 2026: 1.

7 papers.

  1. 2024Chain of Thought Still Thinks Fast: APriCoT Helps with Thinking Slowcited by 8
  2. 2024Investigating Expert-in-the-Loop LLM Discourse Patterns for Ancient Intertextual Analysiscited by 4
  3. 2025How LLMs Comprehend Temporal Meaning in Narratives: A Case Study in Cognitive Evaluation of LLMscited by 3
  4. 2025Investigating Human-Aligned Large Language Model Uncertaintycited by 2
  5. 2025Basic Category Usage in Vision Language Modelscited by 0
  6. 2025Human-Alignment and Calibration of Inference-Time Uncertainty in Large Language Modelscited by 0
  7. 2026Human-Alignment, Calibration, and Activation Patterns in Large Language Model Uncertaintycited by 0