Yaser Al-Onaizan

Beam Search Strategies for Neural Machine Translation

2017

The basic concept in Neural Machine Translation (NMT) is to train a large Neural Network that maximizes the translation performance on a given parallel corpus. NMT is then using a simple left-toright beam-search decoder to …

Zero-Resource Translation with Multi-Lingual Neural Machine Translation

2016 · arXiv (Cornell University)

In this paper, we propose a novel finetuning algorithm for the recently introduced multi-way, mulitlingual neural machine translate that enables zero-resource machine translation. When used together with novel many-to-one translation strategies, we empirically show that …

Temporal Attention Model for Neural Machine Translation

2016 · arXiv (Cornell University)

Attention-based Neural Machine Translation (NMT) models suffer from attention deficiency issues as has been observed in recent research. We propose a novel mechanism to address some of these limitations and improve the NMT attention. Specifically, …

Fast Domain Adaptation for Neural Machine Translation

2016 · arXiv (Cornell University)

Neural Machine Translation (NMT) is a new approach for automatic translation of text from one human language into another. The basic concept in NMT is to train a large Neural Network that maximizes the translation …

Span-Level Model for Relation Extraction

2019

Relation Extraction is the task of identifying entity mention spans in raw text and then identifying relations between pairs of the entity mentions. Recent approaches for this spanlevel task have been token-level models which have …