6 citations · 17 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
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…
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…
Hard Non-Monotonic Attention for Character-Level Transduction
Shijie Wu, Pamela Shapiro, Ryan Cotterell
Character-level string-to-string transduction is an important component of various NLP tasks. The goal is to map an input string to an output string, where the strings may be of di…