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Non-autoregressive (NAR) models can generate sentences with less computation than autoregressive models but sacrifice generation quality.
Binary codes capable of correcting deletions, insertions, and reversals
Vladimir I Levenshtein et al. 1966 · 1966
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A framework of a mechanical translation between japanese and english by analogy principle
Makoto Nagao. 1984 · 1984
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MBT: A memory-based part of speech tagger-generator
Walter Daelemans, Jakub Zavrel, Peter Berck, and Steven Gillis. 1996 · 1996
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Findings of the 2014 workshop on statistical machine translation
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Sequence to sequence learning with neural networks
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Adam: A method for stochastic optimization
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Phrase-level combination of SMT and TM using constrained word lattice
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Neural machine translation of rare words with subword units
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Attention is all you need
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Deterministic non-autoregressive neural sequence modeling by iterative refinement
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Iterative refinement in the continuous space for non-autoregressive neural machine translation
Jason Lee, Raphael Shu, and Kyunghyun Cho. 2020 · 2020
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Boosting neural machine translation with similar translations
Jitao Xu, Josep Crego, and Jean Senellart. 2020 · 2020
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Improving language models by retrieving from trillions of tokens
Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George van den Driessche, Jean-Baptiste Lespiau, Bogdan Damoc, Aidan Clark, Diego de Las Casas, Aurelia Guy, Jacob Menick, Roman Ring, Tom Hennigan, Saffron Huang, Loren Maggiore, Chris Jones, Albin Cassirer, Andy Brock, Michela Paganini, Geoffrey Irving, Oriol Vinyals, Simon Osindero, Karen Simonyan, Jack W. Rae, Erich Elsen, and Laurent Sifre. 2021 · 2021
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Fully non-autoregressive neural machine translation: Tricks of the trade
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Improving non-autoregressive translation models without distillation
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