# Zero-shot learning / zero-shot prompting

Record: term-zero-shot-learning · Type: term · Edition: 0.20.0 · Evidence cutoff: 2026-09-15

[Read in the atlas](https://theaiatlas.org/ideas/zero-shot-learning/) · [Complete evidence](https://theaiatlas.org/evidence.html#idea-zero-shot-learning) · [JSON](https://theaiatlas.org/records/term-zero-shot-learning.json) · [Pinned complete dataset](https://theaiatlas.org/editions/e74392d479c0e7da8636a7d6a0454d03510df86ffca9931eb86babd952665ca5/data.json)

Dataset pointer: `/glossary/111`. Reviewed: 2026-09-15.

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## Publication dates and source age

Source is over 18 months old.

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 establish validity or a new source-reading date. Unknown dates and month/year precision remain explicit in the JSON record.

## /summary

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

Claim: claim-term-zero-shot-learning-1a5192ba3d7825ca26b24a72. Annotation: synthesis.

[glossary-eval-gpt3](https://arxiv.org/html/2005.14165v4)

## /definition

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.

Claim: claim-term-zero-shot-learning-1e4c26398ee834b2e16dc7b8. Annotation: synthesis.

[glossary-eval-gpt3](https://arxiv.org/html/2005.14165v4)

## /placement

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

Claim: claim-term-zero-shot-learning-25f52a21ad9f2e54a62ed1b2. Annotation: editorial.

[glossary-eval-gpt3](https://arxiv.org/html/2005.14165v4)

## /distinction

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

Claim: claim-term-zero-shot-learning-09422ce4d5c74cb753a9bb98. Annotation: synthesis.

[glossary-eval-gpt3](https://arxiv.org/html/2005.14165v4)

## Source provenance

### glossary-eval-gpt3

[Language Models are Few-Shot Learners](https://arxiv.org/html/2005.14165v4)

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

Read scope is described in the source note.

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.

No archive check recorded.