JHU 2019 Robustness Task System Description
暂无分享,去创建一个
[1] Taku Kudo,et al. Subword Regularization: Improving Neural Network Translation Models with Multiple Subword Candidates , 2018, ACL.
[2] Taku Kudo,et al. SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing , 2018, EMNLP.
[3] Graham Neubig,et al. MTNT: A Testbed for Machine Translation of Noisy Text , 2018, EMNLP.
[4] Rico Sennrich,et al. Neural Machine Translation of Rare Words with Subword Units , 2015, ACL.
[5] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[6] Graham Neubig,et al. Pointwise Prediction for Robust, Adaptable Japanese Morphological Analysis , 2011, ACL.
[7] Matt Post,et al. We start by defining the recurrent architecture as implemented in S OCKEYE , following , 2018 .
[8] Kevin Duh,et al. The JHU Machine Translation Systems for WMT 2018 , 2018, WMT.
[9] Huda Khayrallah,et al. Overcoming Catastrophic Forgetting During Domain Adaptation of Neural Machine Translation , 2019, NAACL.
[10] Matt Post,et al. A Call for Clarity in Reporting BLEU Scores , 2018, WMT.
[11] Huda Khayrallah,et al. Regularized Training Objective for Continued Training for Domain Adaptation in Neural Machine Translation , 2018, NMT@ACL.
[12] Philipp Koehn,et al. Findings of the 2015 Workshop on Statistical Machine Translation , 2015, WMT@EMNLP.
[13] Philipp Koehn,et al. Moses: Open Source Toolkit for Statistical Machine Translation , 2007, ACL.
[14] Marcin Junczys-Dowmunt,et al. Dual Conditional Cross-Entropy Filtering of Noisy Parallel Corpora , 2018, WMT.