134 citations · 226 across the 6 of their papers we have counts for
6 papers
Regressing Word and Sentence Embeddings for Regularization of Neural Machine Translation
Inigo Jauregi Unanue, Ehsan Zare Borzeshi, Massimo Piccardi
In recent years, neural machine translation (NMT) has become the dominant approach in automated translation. However, like many other deep learning approaches, NMT suffers from ove…
ReWE: Regressing Word Embeddings for Regularization of Neural Machine Translation Systems
Inigo Jauregi Unanue, Ehsan Zare Borzeshi, Nazanin Esmaili +1
Regularization of neural machine translation is still a significant problem, especially in low-resource settings. To mollify this problem, we propose regressing word embeddings (Re…
A Shared Attention Mechanism for Interpretation of Neural Automatic Post-Editing Systems
Inigo Jauregi Unanue, Ehsan Zare Borzeshi, Massimo Piccardi
Automatic post-editing (APE) systems aim to correct the systematic errors made by machine translators. In this paper, we propose a neural APE system that encodes the source (src) a…
Recurrent neural networks with specialized word embeddings for health-domain named-entity recognition
Inigo Jauregi Unanue, Ehsan Zare Borzeshi, Massimo Piccardi
Background. Previous state-of-the-art systems on Drug Name Recognition (DNR) and Clinical Concept Extraction (CCE) have focused on a combination of text "feature engineering" and c…
Bidirectional LSTM-CRF for Clinical Concept Extraction
Raghavendra Chalapathy, Ehsan Zare Borzeshi, Massimo Piccardi
Automated extraction of concepts from patient clinical records is an essential facilitator of clinical research. For this reason, the 2010 i2b2/VA Natural Language Processing Chall…
Bidirectional LSTM-CRF for Clinical Concept Extraction
Raghavendra Chalapathy, Ehsan Zare Borzeshi, Massimo Piccardi
Extraction of concepts present in patient clinical records is an essential step in clinical research. The 2010 i2b2/VA Workshop on Natural Language Processing Challenges for clinic…