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arXiv's own metadata for 1706.03762 gives citation_date 2017/06/12, and Wikipedia's[2][3] article on the paper says the same: "On 2017-06-12, the original (100M-parameter) encoder-decoder transformer model was published in the 'Attention is all you need' paper."
Dates the paper to 12 June 2017 and describes what it did: "a 2017 research paper on machine learning authored by eight scientists and engineers working at Google" introducing the transformer, "based on the attention mechanism proposed in 2014 by Bahdanau et al.", which "has become the main architecture of a wide variety of artificial intelligence systems, including large language models". It also records that all eight authors later left Google.[1]
The architecture itself, for how self-attention replaced recurrence and what was built on it afterwards.[1]
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