Verified claim · AI-ML · 100% confidence
GloVe introduced in: Pennington, Socher, Manning 2014 — global vectors for word representation.
Last verified 2026-05-16 · Methodology veritas-v0.1 · 7f9254f3c0612ed0
Structured fields
- Subject
- GloVe
- Predicate
introduced_in- Object
- Pennington, Socher, Manning 2014 — global vectors for word representation
- Confidence
- 100%
- Tags
- glove · stanford-nlp · word-embeddings · foundational · 2014 · introduced_in
Sources (2)
[1] peer reviewed · EMNLP 2014 (Pennington, Socher, Manning / Stanford NLP) · 2014-10-25
GloVe: Global Vectors for Word Representation“We propose a new global log-bilinear regression model that combines the advantages of the two major model families in the literature: global matrix factorization and local context window methods. Our model efficiently leverages statistical information by training only on the nonzero elements in a word-word co-occurrence matrix, rather than on the entire sparse matrix or on individual context windows in a large corpus.”
[2] official blog · Stanford NLP Group · 2014-10-25
GloVe — Stanford NLP project page
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curl https://sourcescore.org/api/v1/claims/7f9254f3c0612ed0.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/7f9254f3c0612ed0.json");
const envelope = await r.json();
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// "GloVe introduced in: Pennington, Socher, Manning 2014 — global vectors for word representation."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/7f9254f3c0612ed0.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "GloVe introduced in: Pennington, Socher, Manning 2014 — global vectors for word representation."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_glove_fact() -> dict:
"""Fetch the verified SourceScore claim for GloVe."""
r = httpx.get("https://sourcescore.org/api/v1/claims/7f9254f3c0612ed0.json")
return r.json()