Claim · 2020-05-28 · event · Stated in source · Supported

The GPT-3 paper (arXiv v1, 2020) uses "a large language model" of the model in work it cites as [RRS20].

One recorded claim. The claim panel gives its qualification, the source passages with their place in each source, and how it was checked.

What it connects

Language Models are Few-Shot Learners → uses the name →

Where it appears

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Claim and evidence

Language Models are Few-Shot Learnersuses the name ↓

Machine-checked, not reviewed by an editorStated in sourceSupported

Supporting evidence: primary · 1 source

Date: 2020-05-28 · event Records dated 2020 →

Scope and limitsA use in passing; the paper calls GPT-3 itself "an autoregressive language model with 175 billion parameters".

The evidence 01

primary sourceSupports the claim

Language Models are Few-Shot Learners

arXiv · 2020-05-28

Cite the original source

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Source excerpt

“[RRS20] recently demonstrated that a large language model can perform surprisingly well directly answering the questions without conditioning on auxilliary information.”

Location in source PDF p. 13, section 3.3

How it was read Retrieved directly from the publisher

Machine-checked · 2026-10-31

Source details and check notes

Authors: Tom B. Brown; Benjamin Mann; Nick Ryder; Melanie Subbiah; Jared Kaplan; Prafulla Dhariwal; Arvind Neelakantan; Pranav Shyam; Girish Sastry; Amanda Askell; Sandhini Agarwal; Ariel Herbert-Voss; Gretchen Krueger; Tom Henighan; Rewon Child; Aditya Ramesh; Daniel M. Ziegler; Jeffrey Wu; Clemens Winter; Christopher Hesse; Mark Chen; Eric Sigler; Mateusz Litwin; Scott Gray; Benjamin Chess; Jack Clark; Christopher Berner; Sam McCandlish; Alec Radford; Ilya Sutskever; Dario Amodei
Version: arXiv:2005.14165v1, submitted 28 May 2020 (UTC). Retrieved for the candidate pack on 2026-10-28 (SHA-256 f756a2d3e23c2770a3e8c4354965e98d37411c18aab91556df0c335675dec396). The author list is the byline as printed on the first page.
Version date: 2020-05-28
Canonical address: Open the canonical source ↗
Accessed: 2026-10-28
Language: English (en)
Attribution: Tom B. Brown and others, “Language Models are Few-Shot Learners”, 2020-05-28.
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, Kinds of AI and technical history (research/technical-history). The quotation (21 words) matched the text retrieved for the candidate pack on 2026-10-29. Matching ignored differences of whitespace, case, quotation marks, dashes, PDF line-break hyphens 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 uses a name for a family of methods or a term, in the sense the concept’s naming criterion describes or, where labelled, in another sense. The record documents the use; it is not evidence that the name began there, and it implies no influence on or from another text.

Date. Date of submission (an arXiv version or a journal’s received date, as the source states it); not a later revision or the venue’s publication date.

Record ID th-term-llm-gpt3-2020