Verified claim · AI-ML · 100% confidence
Flamingo introduced in: Alayrac et al. 2022 — DeepMind few-shot vision-language model.
Last verified 2026-05-16 · Methodology veritas-v0.1 · 72ea74efc723bd06
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Structured fields
- Subject
- Flamingo
- Predicate
introduced_in- Object
- Alayrac et al. 2022 — DeepMind few-shot vision-language model
- Confidence
- 100%
- Tags
- flamingo · deepmind · vision-language · few-shot · multimodal · 2022 · introduced_in
Sources (2)
[1] preprint · arXiv (Alayrac, Donahue, Luc, Miech, Barr, Hasson, Lenc, Mensch, Millican, et al. / DeepMind) · 2022-04-29
Flamingo: a Visual Language Model for Few-Shot Learning“We introduce Flamingo, a family of Visual Language Models (VLM) with this ability. We propose key architectural innovations to: (i) bridge powerful pretrained vision-only and language-only models, (ii) handle sequences of arbitrarily interleaved visual and textual data, and (iii) seamlessly ingest images or videos as inputs.”
[2] official blog · Google DeepMind · 2022-04-29
Tackling multiple tasks with a single visual language modelGoogle DeepMind is rated by SourceScore — see its reliability →
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Flamingo introduced in: Alayrac et al. 2022 — DeepMind few-shot vision-language model. — SourceScore Claim 72ea74efc723bd06 (verified 2026-05-16). https://sourcescore.org/api/v1/claims/72ea74efc723bd06.jsonEmbed this claim
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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.
What is the evidence for "Flamingo introduced in: Alayrac et al. 2022 — DeepMind few-shot vision-language model."?
Evidence comes from 2 primary sources: arXiv (Alayrac, Donahue, Luc, Miech, Barr, Hasson, Lenc, Mensch, Millican, et al. / DeepMind), Google DeepMind. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/72ea74efc723bd06.json includes an HMAC-SHA256 signature for audit verification.
When was this claim last verified by SourceScore?
Last verified 2026-05-16 under methodology version veritas-v0.1. The signed JSON envelope is dated and cryptographically signed for audit trail. Re-verification cadence depends on the claim type and source freshness.
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cURL
curl https://sourcescore.org/api/v1/claims/72ea74efc723bd06.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/72ea74efc723bd06.json");
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// "Flamingo introduced in: Alayrac et al. 2022 — DeepMind few-shot vision-language model."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/72ea74efc723bd06.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "Flamingo introduced in: Alayrac et al. 2022 — DeepMind few-shot vision-language model."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_flamingo_fact() -> dict:
"""Fetch the verified SourceScore claim for Flamingo."""
r = httpx.get("https://sourcescore.org/api/v1/claims/72ea74efc723bd06.json")
return r.json()