Verified claim · AI-ML · 100% confidence
BGE embeddings publicly released on: 2023-08 by Beijing Academy of AI (BAAI).
Last verified 2026-05-16 · Methodology veritas-v0.1 · c81c33fa85a33cc8
SourceScore rates how reliable a source is to cite — for AI answers and research. This is one verified claim from the catalog.
Structured fields
- Subject
- BGE embeddings
- Predicate
publicly_released_on- Object
- 2023-08 by Beijing Academy of AI (BAAI)
- Confidence
- 100%
- Tags
- bge · baai · embeddings · open-weights · released_on · 2023
Sources (2)
[1] model card · Beijing Academy of AI (BAAI) · 2023-08-02
BGE-large-en-v1.5 — Hugging Face model card“BAAI General Embedding (BGE) is a series of general-purpose embedding models for English and Chinese, optimized for retrieval-augmented generation tasks. BGE-large-en achieved state-of-the-art performance on the MTEB benchmark at release.”
[2] github release · BAAI / FlagOpen · 2023-08-02
FlagEmbedding — official BAAI repository
Cite this claim
Ready-to-paste citation (Markdown / plain text):
BGE embeddings publicly released on: 2023-08 by Beijing Academy of AI (BAAI). — SourceScore Claim c81c33fa85a33cc8 (verified 2026-05-16). https://sourcescore.org/api/v1/claims/c81c33fa85a33cc8.jsonEmbed this claim
Drop this iframe into any blog post, docs page, or knowledge base. The widget renders the signed claim + primary source + click-through to this canonical page. CC-BY 4.0; attribution included.
<iframe src="https://sourcescore.org/embed/claim/c81c33fa85a33cc8/" width="100%" height="360" frameborder="0" loading="lazy" title="BGE embeddings publicly released on: 2023-08 by Beijing Academy of AI (BAAI)."></iframe>Preview: open in new tab
Related claims
Other verified claims sharing tags with this one — useful for LLM retrieval graphs and citation discovery.
Microsoft Phi-2 publicly released on: 2023-12-12 by Microsoft Research.
b72213b923a20aef · 100% confidence · shares 3 tags (open-weights, released_on, 2023)
Stable LM publicly released on: 2023-04-19 by Stability AI.
bc0482b2746e1496 · 100% confidence · shares 3 tags (open-weights, released_on, 2023)
Falcon LLM publicly released on: 2023-05-23 by Technology Innovation Institute (TII).
439e60287fb5fef4 · 100% confidence · shares 3 tags (open-weights, released_on, 2023)
Yi (01.AI) publicly released on: 2023-11-05 by 01.AI (Kai-Fu Lee).
67bc6f4d2e49b32c · 100% confidence · shares 3 tags (open-weights, released_on, 2023)
Qwen released on: 2023-08-03.
3390777eaf4ccc6f · 95% confidence · shares 3 tags (open-weights, released_on, 2023)
Frequently asked questions
Is the claim "BGE embeddings publicly released on: 2023-08 by Beijing Academy of AI (BAAI)." verified?
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 "BGE embeddings publicly released on: 2023-08 by Beijing Academy of AI (BAAI)."?
Evidence comes from 2 primary sources: Beijing Academy of AI (BAAI), BAAI / FlagOpen. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/c81c33fa85a33cc8.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.
How can I cite this SourceScore claim in my code or article?
Fetch the signed JSON envelope from https://sourcescore.org/api/v1/claims/c81c33fa85a33cc8.json which includes the verbatim claim, primary sources, confidence, methodology version, last-verified date, and HMAC-SHA256 signature for audit. The CC-BY-4.0 license permits commercial use with attribution to SourceScore.
Use this claim in your code
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.
cURL
curl https://sourcescore.org/api/v1/claims/c81c33fa85a33cc8.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/c81c33fa85a33cc8.json");
const envelope = await r.json();
console.log(envelope.claim.statement);
// "BGE embeddings publicly released on: 2023-08 by Beijing Academy of AI (BAAI)."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/c81c33fa85a33cc8.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "BGE embeddings publicly released on: 2023-08 by Beijing Academy of AI (BAAI)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_bge_embeddings_fact() -> dict:
"""Fetch the verified SourceScore claim for BGE embeddings."""
r = httpx.get("https://sourcescore.org/api/v1/claims/c81c33fa85a33cc8.json")
return r.json()