Verified claim · AI-ML · 100% confidence
MTEB benchmark introduced in: Muennighoff et al. 2022 — Massive Text Embedding Benchmark.
Last verified 2026-05-16 · Methodology veritas-v0.1 · cccd161dd058a31e
Structured fields
- Subject
- MTEB benchmark
- Predicate
introduced_in- Object
- Muennighoff et al. 2022 — Massive Text Embedding Benchmark
- Confidence
- 100%
- Tags
- mteb · benchmark · embeddings · huggingface · evaluation · 2022 · introduced_in
Sources (2)
[1] preprint · arXiv (Muennighoff, Tazi, Magne, Reimers / Hugging Face + ContextualAI) · 2022-10-13
MTEB: Massive Text Embedding Benchmark“Text embeddings are commonly evaluated on a small set of datasets from a single task not covering their possible applications to other tasks. It is unclear whether state-of-the-art embeddings on semantic textual similarity (STS) can be equally well applied to other tasks like clustering or reranking.”
[2] official blog · Hugging Face / MTEB community · 2022-10-13
MTEB Leaderboard — live ranking on Hugging Face
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MTEB benchmark introduced in: Muennighoff et al. 2022 — Massive Text Embedding Benchmark. — SourceScore Claim cccd161dd058a31e (verified 2026-05-16). https://sourcescore.org/api/v1/claims/cccd161dd058a31e.jsonEmbed this claim
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Fetch this signed envelope from your application. The response includes the verbatim excerpt, primary source URLs, and an HMAC-SHA256 signature you can verify locally for audit trails.
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curl https://sourcescore.org/api/v1/claims/cccd161dd058a31e.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/cccd161dd058a31e.json");
const envelope = await r.json();
console.log(envelope.claim.statement);
// "MTEB benchmark introduced in: Muennighoff et al. 2022 — Massive Text Embedding Benchmark."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/cccd161dd058a31e.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "MTEB benchmark introduced in: Muennighoff et al. 2022 — Massive Text Embedding Benchmark."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_mteb_benchmark_fact() -> dict:
"""Fetch the verified SourceScore claim for MTEB benchmark."""
r = httpx.get("https://sourcescore.org/api/v1/claims/cccd161dd058a31e.json")
return r.json()