Language Models not just for Pre-training: Fast Online Neural Noisy Channel Modeling
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Sergey Edunov | Michael Auli | Kyra Yee | Shruti Bhosale | Michael Auli | Sergey Edunov | Shruti Bhosale | Kyra Yee
[1] Vishrav Chaudhary,et al. CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data , 2019, LREC.
[2] Yann Dauphin,et al. Pay Less Attention with Lightweight and Dynamic Convolutions , 2019, ICLR.
[3] Myle Ott,et al. Scaling Neural Machine Translation , 2018, WMT.
[4] Marjan Ghazvininejad,et al. Multilingual Denoising Pre-training for Neural Machine Translation , 2020, Transactions of the Association for Computational Linguistics.
[5] Rico Sennrich,et al. Neural Machine Translation of Rare Words with Subword Units , 2015, ACL.
[6] Jason Weston,et al. Don't Say That! Making Inconsistent Dialogue Unlikely with Unlikelihood Training , 2020, ACL.
[7] Myle Ott,et al. Understanding Back-Translation at Scale , 2018, EMNLP.
[8] Daniel Marcu,et al. Statistical Phrase-Based Translation , 2003, NAACL.
[9] Zhiguo Wang,et al. Vocabulary Manipulation for Neural Machine Translation , 2016, ACL.
[10] Rico Sennrich,et al. Improving Neural Machine Translation Models with Monolingual Data , 2015, ACL.
[11] Jungo Kasai,et al. Deep Encoder, Shallow Decoder: Reevaluating the Speed-Quality Tradeoff in Machine Translation , 2020, ArXiv.
[12] Peng-Jen Chen,et al. Facebook AI’s WAT19 Myanmar-English Translation Task Submission , 2019, EMNLP.
[13] Alec Radford,et al. Improving Language Understanding by Generative Pre-Training , 2018 .
[14] David Grangier,et al. Vocabulary Selection Strategies for Neural Machine Translation , 2016, ArXiv.
[15] Myle Ott,et al. fairseq: A Fast, Extensible Toolkit for Sequence Modeling , 2019, NAACL.
[16] Colin Raffel,et al. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer , 2019, J. Mach. Learn. Res..
[17] Timothy Baldwin,et al. langid.py: An Off-the-shelf Language Identification Tool , 2012, ACL.
[18] Veselin Stoyanov,et al. Simple Fusion: Return of the Language Model , 2018, WMT.
[19] Matt Post,et al. A Call for Clarity in Reporting BLEU Scores , 2018, WMT.
[20] Edouard Grave,et al. Reducing Transformer Depth on Demand with Structured Dropout , 2019, ICLR.
[21] Veselin Stoyanov,et al. Unsupervised Cross-lingual Representation Learning at Scale , 2019, ACL.
[22] Robert L. Mercer,et al. The Mathematics of Statistical Machine Translation: Parameter Estimation , 1993, CL.
[23] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[24] Myle Ott,et al. Facebook FAIR’s WMT19 News Translation Task Submission , 2019, WMT.
[25] Sergey Edunov,et al. Pre-trained language model representations for language generation , 2019, NAACL.
[26] Dan Klein,et al. Conditional Structure versus Conditional Estimation in NLP Models , 2002, EMNLP.
[27] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[28] Ondrej Bojar,et al. Improving Translation Model by Monolingual Data , 2011, WMT@EMNLP.
[29] Philipp Koehn,et al. Moses: Open Source Toolkit for Statistical Machine Translation , 2007, ACL.
[30] Rico Sennrich,et al. Edinburgh Neural Machine Translation Systems for WMT 16 , 2016, WMT.
[31] Yoshua Bengio,et al. On Using Monolingual Corpora in Neural Machine Translation , 2015, ArXiv.
[32] Nathan Ng,et al. Simple and Effective Noisy Channel Modeling for Neural Machine Translation , 2019, EMNLP.
[33] Jiajun Shen,et al. Revisiting Self-Training for Neural Sequence Generation , 2020, ICLR.
[34] Edouard Grave,et al. Depth-Adaptive Transformer , 2020, ICLR.
[35] Wang Ling,et al. Better Document-Level Machine Translation with Bayes’ Rule , 2019, Transactions of the Association for Computational Linguistics.
[36] Lei Yu,et al. The Neural Noisy Channel , 2016, ICLR.