Claim and evidence Close ×
Shanahan's paper of December 2022 states that a large language model is a generative mathematical model of the statistical distribution of tokens in human-generated text, which simply generates statistically likely sequences of words, and that a simple LLM-based question-answering system does not properly speaking have beliefs. Copy claim link
Copy claim reference
Machine-checked, not reviewed by an editor Stated in source Supported
Supporting evidence: primary · 1 source; Context: primary · 1 source
Date 2022-12-07 · publication Records dated 2022 → Role Articulation Register (kind of text) Nonfiction Scope and limits The paper states that it does not argue that an LLM-based system could never warrant description in terms of beliefs or intentions, and treats systems embedded in larger systems separately.
The evidence 04 primary source Supports the claim
Talking About Large Language Models ↗ arXiv preprint 2212.03551 · 2022-12-07
Copy source reference
Cite the original source Cite the original document, not Selekoa. Check these details against it.
Copy APA
Download BibTeX Download RIS Download CSL-JSON
Source excerpt “LLMs are generative mathematical models of the statistical distribution of tokens in the vast public corpus of human-generated text” Location in source Section 2, PDF p. 2
How it was read Retrieved directly from the publisher
Machine-checked · 2026-10-31
Source details and check notes Authors Murray Shanahan Version Retrieved for the candidate pack on 2026-10-29 (SHA-256 3324123876e9e9f1fbfc6f635acb247cf0b7a549c98db207f5dbbbf91a32e10a). arXiv v1 of 7 December 2022. Canonical address Open the canonical source ↗ Accessed 2026-10-29 Language English (en) Attribution Murray Shanahan, “Talking About Large Language Models”, 2022-12-07. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, arguments about catastrophic risk from advanced AI (research/risk-debate). The quotation (19 words) matched the text retrieved for the candidate pack on 2026-10-29. Matching ignored differences of whitespace, case, quotation marks, dashes and Unicode compatibility forms, so the source’s typography can differ. No human editorial review. primary source Supports the claim
Talking About Large Language Models ↗ arXiv preprint 2212.03551 · 2022-12-07
Copy source reference
Cite the original source Cite the original document, not Selekoa. Check these details against it.
Copy APA
Download BibTeX Download RIS Download CSL-JSON
Source excerpt “what the LLM actually does, which is simply to generate statistically likely sequences of words” Location in source Section 2, PDF p. 2
How it was read Retrieved directly from the publisher
Machine-checked · 2026-10-31
Source details and check notes Authors Murray Shanahan Version Retrieved for the candidate pack on 2026-10-29 (SHA-256 3324123876e9e9f1fbfc6f635acb247cf0b7a549c98db207f5dbbbf91a32e10a). arXiv v1 of 7 December 2022. Canonical address Open the canonical source ↗ Accessed 2026-10-29 Language English (en) Attribution Murray Shanahan, “Talking About Large Language Models”, 2022-12-07. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, arguments about catastrophic risk from advanced AI (research/risk-debate). The quotation (15 words) matched the text retrieved for the candidate pack on 2026-10-29. Matching ignored differences of whitespace, case, quotation marks, dashes and Unicode compatibility forms, so the source’s typography can differ. No human editorial review. primary source Supports the claim
Talking About Large Language Models ↗ arXiv preprint 2212.03551 · 2022-12-07
Copy source reference
Cite the original source Cite the original document, not Selekoa. Check these details against it.
Copy APA
Download BibTeX Download RIS Download CSL-JSON
Source excerpt “a simple LLM-based question-answering system like BOT does not properly speaking have beliefs” Location in source Section 5, PDF p. 4
How it was read Retrieved directly from the publisher
Machine-checked · 2026-10-31
Source details and check notes Authors Murray Shanahan Version Retrieved for the candidate pack on 2026-10-29 (SHA-256 3324123876e9e9f1fbfc6f635acb247cf0b7a549c98db207f5dbbbf91a32e10a). arXiv v1 of 7 December 2022. Canonical address Open the canonical source ↗ Accessed 2026-10-29 Language English (en) Attribution Murray Shanahan, “Talking About Large Language Models”, 2022-12-07. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, arguments about catastrophic risk from advanced AI (research/risk-debate). The quotation (13 words) matched the text retrieved for the candidate pack on 2026-10-29. Matching ignored differences of whitespace, case, quotation marks, dashes and Unicode compatibility forms, so the source’s typography can differ. No human editorial review. primary source Context only
Talking About Large Language Models ↗ arXiv preprint 2212.03551 · 2022-12-07
Copy source reference
Cite the original source Cite the original document, not Selekoa. Check these details against it.
Copy APA
Download BibTeX Download RIS Download CSL-JSON
Source excerpt “it is not the argument of this paper that a system based on a large language model could never, in principle, warrant description in terms of beliefs, intentions, reason, etc.” Location in source Section 3, PDF p. 3
How it was read Retrieved directly from the publisher
Machine-checked · 2026-10-31
Source details and check notes Authors Murray Shanahan Version Retrieved for the candidate pack on 2026-10-29 (SHA-256 3324123876e9e9f1fbfc6f635acb247cf0b7a549c98db207f5dbbbf91a32e10a). arXiv v1 of 7 December 2022. Canonical address Open the canonical source ↗ Accessed 2026-10-29 Language English (en) Attribution Murray Shanahan, “Talking About Large Language Models”, 2022-12-07. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, arguments about catastrophic risk from advanced AI (research/risk-debate). The quotation (30 words) matched the text retrieved for the candidate pack on 2026-10-29. Matching ignored differences of whitespace, case, quotation marks, dashes and Unicode compatibility forms, so the source’s typography can differ. No human editorial review. Status and meaning Editorial status. Not reviewed by an editor . An exploratory record that no editor has accepted. This status does not say whether a person has read any linked passage. Each evidence record above shows how it was checked.
Relation. A passage of the document meets the proposition’s criterion. The record documents what the text states, in its register (fiction and satire are labelled); it is not evidence that the proposition is true and implies no influence on or from another text.
Date. Date of the arXiv v1 submission.
Record ID rd-r14-shanahan-2022-talking-about-llms