Research breakthrough · curated entry
Sequence to sequence learning makes end-to-end translation possible
Sequence to Sequence Learning with Neural Networks
- Date
- September 10, 2014
- Category
- Research breakthrough
- Organization / Model
- Evidence
- 1 source · 1 evidence family
Sutskever and colleagues proposed mapping a variable-length input to a variable-length output with two recurrent networks. It became the key architectural basis for machine translation and later for dialogue systems.
Curator's note: Cross-checked against the arXiv paper.
Curated sources · 1
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This page is a curated static snapshot and can be cited directly. Preferred format GB/T 7714—2025 (electronic resource [EB/OL]); the other 5 styles open below, together with the machine-readable files.
GB/T 7714—2025 (electronic resource [EB/OL])
AI 纪年. 序列到序列学习提出，端到端翻译成为可能[EB/OL]. (2014-09-10)[2026-11-03]. https://aihist.net/e/seq2seq-2014.html.
APA 7 · American Psychological Association
AI 纪年. (2014, September 10). 序列到序列学习提出，端到端翻译成为可能 [Web page]. https://aihist.net/e/seq2seq-2014.html
MLA 9 · Modern Language Association
"序列到序列学习提出，端到端翻译成为可能." AI 纪年, 10 Sept. 2014, aihist.net/e/seq2seq-2014.html. Accessed 3 Nov. 2026.
Chicago 17 · notes-bibliography
AI 纪年. "序列到序列学习提出，端到端翻译成为可能." Published Sept. 10, 2014. Accessed Nov. 3, 2026. https://aihist.net/e/seq2seq-2014.html.
IEEE · citation-reference list
"序列到序列学习提出，端到端翻译成为可能," AI 纪年, 10 Sept. 2014. [Online]. Available: https://aihist.net/e/seq2seq-2014.html. [Accessed: 3 Nov. 2026].
ACM · author-date variant
AI 纪年. September 10, 2014. 序列到序列学习提出，端到端翻译成为可能. Retrieved November 3, 2026 from https://aihist.net/e/seq2seq-2014.html.
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