![The Transformer architecture [29] in an encoder-decoder setting ...](https://www.researchgate.net/profile/Lars-Bentsen/publication/363085057/figure/fig5/AS:11431281081500365@1661837233522/FFTransformer-in-an-encoder-decoder-setting-Two-streams-focus-on-trend-and-periodic_Q640.jpg)
%2C%20encodes%20the%20input%20once%20and%20decodes%20the%20output%20in%20parallel%2C%20boosting%20both%20training%20and%20inference%20efficiency%20by%20avoiding%20duplicate%20input%20encoding%20and%20increasing%20the%20operational%20intensity%20(ratio%20of%20numbers%20of%20arithmetic%20operation%20to%20memory%20access)%20of%20decoding%20process%20by%20sharing%20the%20input%20key-value%20cache.%20We%20achieve%20computation%20reduction%20that%20roughly%20scales%20with%20the%20number%20of%20subtasks%2C%20gaining%20up%20to%204.6x%20speed-up%20over%20state-of-the-art%20models%20for%20dialogue%20state%20tracking%2C%20summarization%2C%20and%20question-answering%20tasks%2C%20with%20comparable%20or%20better%20performance.)
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