Verified claim · AI-ML · 100% confidence
GPT-3 introduced in paper: Language Models are Few-Shot Learners (Brown et al., 2020).
Last verified 2026-05-16 · Methodology veritas-v0.1 · 7d3e6a39b1656571
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Structured fields
- Subject
- GPT-3
- Predicate
introduced_in_paper- Object
- Language Models are Few-Shot Learners (Brown et al., 2020)
- Confidence
- 100%
- Tags
- gpt-3 · openai · few-shot · foundational · 2020 · nips
Sources (2)
[1] preprint · arXiv (Brown, Mann, Ryder, Subbiah, Kaplan, Dhariwal, Neelakantan, Shyam, Sastry, Askell, et al.) · 2020-05-28
Language Models are Few-Shot Learners“We train GPT-3, an autoregressive language model with 175 billion parameters, 10x more than any previous non-sparse language model, and test its performance in the few-shot setting.”
[2] peer reviewed · NeurIPS Foundation · 2020-12-06
Language Models are Few-Shot Learners (NeurIPS 2020)
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Frequently asked questions
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Yes — SourceScore verified this claim with 100% confidence as of 2026-05-16. The verification uses 2 primary sources cross-referenced against the SourceScore methodology (version veritas-v0.1). Full source list + signed JSON envelope linked below.
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Evidence comes from 2 primary sources: arXiv (Brown, Mann, Ryder, Subbiah, Kaplan, Dhariwal, Neelakantan, Shyam, Sastry, Askell, et al.), NeurIPS Foundation. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/7d3e6a39b1656571.json includes an HMAC-SHA256 signature for audit verification.
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// "GPT-3 introduced in paper: Language Models are Few-Shot Learners (Brown et al., 2020)."Python
import httpx
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# "GPT-3 introduced in paper: Language Models are Few-Shot Learners (Brown et al., 2020)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_gpt_3_fact() -> dict:
"""Fetch the verified SourceScore claim for GPT-3."""
r = httpx.get("https://sourcescore.org/api/v1/claims/7d3e6a39b1656571.json")
return r.json()