mlsanityData to 7 Oct 2026

Are Language Models More Like Libraries or Like Librarians? Bibliotechnism, the Novel Reference Problem, and the Attitudes of LLMs

arXiv 2401.04854 ↗First posted 10 Jan 2024cs.CLcited by 11

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Abstract (arXiv)

Are LLMs cultural technologies like photocopiers or printing presses, which transmit information but cannot create new content? A challenge for this idea, which we call bibliotechnism, is that LLMs generate novel text. We begin with a defense of bibliotechnism, showing how even novel text may inherit its meaning from original human-generated text. We then argue that bibliotechnism faces an independent challenge from examples in which LLMs generate novel reference, using new names to refer to new entities. Such examples could be explained if LLMs were not cultural technologies but had beliefs, desires, and intentions. According to interpretationism in the philosophy of mind, a system has such attitudes if and only if its behavior is well explained by the hypothesis that it does. Interpretationists may hold that LLMs have attitudes, and thus have a simple solution to the novel reference problem. We emphasize, however, that interpretationism is compatible with very simple creatures having attitudes and differs sharply from views that presuppose these attitudes require consciousness, sentience, or intelligence (topics about which we make no claims).

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 26 of its 72 references that are in the map. First posted on arXiv 10 Jan 2024.

Builds on

26 of 72 references.

References · 26

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14 more
  1. 2021How much do language models copy from their training data? Evaluating linguistic novelty in text generation using RAVENcited by 124
  2. 2023Interpretability at Scale: Identifying Causal Mechanisms in Alpacacited by 102
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  5. 2023Still No Lie Detector for Language Models: Probing Empirical and Conceptual Roadblockscited by 77
  6. 2022Meaning without reference in large language modelscited by 76
  7. 2023Could a Large Language Model be Conscious?cited by 70
  8. 2022Do Large Language Models know what humans know?cited by 60
  9. 2020Word meaning in minds and machinescited by 51
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 4; 2025: 2; 2026: 5.

11 papers.