6 citations · 6 across the 1 of their papers we have counts for
3 papers
cs.CL2019★ 6 cited
Curriculum Learning for Domain Adaptation in Neural Machine Translation
Xuan Zhang, Pamela Shapiro, Gaurav Kumar +3
We introduce a curriculum learning approach to adapt generic neural machine translation models to a specific domain. Samples are grouped by their similarities to the domain of inte…
cs.CL2018
BPE and CharCNNs for Translation of Morphology: A Cross-Lingual Comparison and Analysis
Pamela Shapiro, Kevin Duh
Neural Machine Translation (NMT) in low-resource settings and of morphologically rich languages is made difficult in part by data sparsity of vocabulary words. Several methods have…
cs.CL2018
Character-Aware Decoder for Translation into Morphologically Rich Languages
Adithya Renduchintala, Pamela Shapiro, Kevin Duh +1
Neural machine translation (NMT) systems operate primarily on words (or sub-words), ignoring lower-level patterns of morphology. We present a character-aware decoder designed to ca…