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cs.CL2022
DiMS: Distilling Multiple Steps of Iterative Non-Autoregressive Transformers for Machine Translation
Sajad Norouzi, Rasa Hosseinzadeh, Felipe Perez +1
The computational benefits of iterative non-autoregressive transformers decrease as the number of decoding steps increases. As a remedy, we introduce Distill Multiple Steps (DiMS),…
cs.CL2017★ 4 cited
Unsupervised Document Embedding With CNNs
Chundi Liu, Shunan Zhao, Maksims Volkovs
We propose a new model for unsupervised document embedding. Leading existing approaches either require complex inference or use recurrent neural networks (RNN) that are difficult t…