Verified claim · AI-ML · 82% confidence
Additive (Bahdanau) attention introduced in paper: Neural Machine Translation by Jointly Learning to Align and Translate (Bahdanau et al., 2014).
Last verified 2026-06-01 · Methodology veritas-v0.1 · bbf65d37f2df1971
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Structured fields
- Subject
- Additive (Bahdanau) attention
- Predicate
introduced_in_paper- Object
- Neural Machine Translation by Jointly Learning to Align and Translate (Bahdanau et al., 2014)
- Confidence
- 82%
- Tags
- attention · bahdanau · alignment · neural-machine-translation · seq2seq · foundational · 2014
Sources (2)
[1] preprint · arXiv (Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio) · 2014-09-01
Neural Machine Translation by Jointly Learning to Align and Translate“Neural machine translation is a recently proposed approach to machine translation. Unlike the traditional statistical machine translation, the neural machine translation aims at building a single neural network that can be jointly tuned to maximize the translation performance.”
[2] docs · Hugging Face
Neural Machine Translation by Jointly Learning to Align and Translate (Hugging Face Papers)Hugging Face is rated by SourceScore — see its reliability →
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curl https://sourcescore.org/api/v1/claims/bbf65d37f2df1971.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/bbf65d37f2df1971.json");
const envelope = await r.json();
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// "Additive (Bahdanau) attention introduced in paper: Neural Machine Translation by Jointly Learning to Align and Translate (Bahdanau et al., 2014)."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/bbf65d37f2df1971.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "Additive (Bahdanau) attention introduced in paper: Neural Machine Translation by Jointly Learning to Align and Translate (Bahdanau et al., 2014)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_additive_bahdanau_attention_fact() -> dict:
"""Fetch the verified SourceScore claim for Additive (Bahdanau) attention."""
r = httpx.get("https://sourcescore.org/api/v1/claims/bbf65d37f2df1971.json")
return r.json()