Verified claim · AI-ML · 82% confidence
ALBERT introduced in paper: ALBERT: A Lite BERT for Self-supervised Learning of Language Representations (Lan et al., 2019).
Last verified 2026-06-02 · Methodology veritas-v0.1 · 7c050ea8dac8797e
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Structured fields
- Subject
- ALBERT
- Predicate
introduced_in_paper- Object
- ALBERT: A Lite BERT for Self-supervised Learning of Language Representations (Lan et al., 2019)
- Confidence
- 82%
- Tags
- albert · bert · language-model · parameter-reduction · lan · google · foundational · 2019
Sources (2)
[1] preprint · arXiv (Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, Radu Soricut) · 2019-09-26
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations“To address these problems, we present two parameter-reduction techniques to lower memory consumption and increase the training speed of BERT.”
[2] docs · Hugging Face
ALBERT (Hugging Face Papers)Hugging Face is rated by SourceScore — see its reliability →
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const r = await fetch("https://sourcescore.org/api/v1/claims/7c050ea8dac8797e.json");
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// "ALBERT introduced in paper: ALBERT: A Lite BERT for Self-supervised Learning of Language Representations (Lan et al., 2019)."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/7c050ea8dac8797e.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "ALBERT introduced in paper: ALBERT: A Lite BERT for Self-supervised Learning of Language Representations (Lan et al., 2019)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_albert_fact() -> dict:
"""Fetch the verified SourceScore claim for ALBERT."""
r = httpx.get("https://sourcescore.org/api/v1/claims/7c050ea8dac8797e.json")
return r.json()