A field guide to AI positions

Zero-shot learning / zero-shot prompting

Prompting method.

Source is over 18 months old.

Publication dates and source age

Sources counted: 1

Newest dated source: 2020-05-28

Assessed at this edition's evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.

Publication age does not tell us whether a claim is still valid. Reading an old source again does not make its publication date newer. An update date does not establish that the passage we used was updated.

Open in the glossary Reading notes · Structured record

Prepared with AI assistance. Not independently fact-checked. Original sources and qualifications are below.

In plain language

Asking a model to perform a task without giving worked examples in that prompt. [1]

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Explanation based on the linked sources. Claim ID: claim-term-zero-shot-learning-1a5192ba3d7825ca26b24a72. Edition 0.20.0.

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Limits & distinctions

Zero-shot does not mean untrained, unfamiliar with the topic, or free of test contamination. It describes the immediate task setup. [1]

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Explanation based on the linked sources. Claim ID: claim-term-zero-shot-learning-09422ce4d5c74cb753a9bb98. Edition 0.20.0.

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A fuller explanation

For an LLM, a zero-shot test might give an instruction and a question but no demonstration of a correct answer. This tests what the already-trained model can do under that setup. [1]

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Explanation based on the linked sources. Claim ID: claim-term-zero-shot-learning-1e4c26398ee834b2e16dc7b8. Edition 0.20.0.

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How it relates to the map

Atlas reading question: does a comparison use the same amount of help in each model's input? [1]

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Editorial interpretation or qualification. Claim ID: claim-term-zero-shot-learning-25f52a21ad9f2e54a62ed1b2. Edition 0.20.0.

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https://theaiatlas.org/ideas/zero-shot-learning/

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Sources and what we read

  1. 1. Language Models are Few-Shot Learners

    Tom B. Brown and coauthors / arXiv · First-hand source · Published 2020-05-28 · Updated 2020-07-22 · Material last read 2026-09-15

    Source is over 18 months old.

    Publication dates and source age

    Sources counted: 1

    Newest dated source: 2020-05-28

    Assessed at this edition's evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.

    Publication age does not tell us whether a claim is still valid. Reading an old source again does not make its publication date newer. An update date does not establish that the passage we used was updated.

    Read scope is described in the source note.

    No archive check recorded.

    Read the abstract, section 2 on zero-shot and few-shot settings, and section 4 on training-data overlap. Version 4 is dated 22 July 2020. The reported results concern GPT-3 and are not current model rankings; detected overlap did not uniformly inflate scores.

    Source ID: glossary-eval-gpt3

Edition and machine-readable evidence

Content version 0.20.0. Evidence cutoff 2026-09-15; this does not mean every source was read on that day.

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