343 citations · 1.3k across the 50 of their papers we have counts for
8 papers · 1 filter
Explaining Sequence-Level Knowledge Distillation as Data-Augmentation for Neural Machine Translation
Mitchell A. Gordon, Kevin Duh
Sequence-level knowledge distillation (SLKD) is a model compression technique that leverages large, accurate teacher models to train smaller, under-parameterized student models. Wh…
Multilingual End-to-End Speech Translation
Hirofumi Inaguma, Kevin Duh, Tatsuya Kawahara +1
In this paper, we propose a simple yet effective framework for multilingual end-to-end speech translation (ST), in which speech utterances in source languages are directly translat…
Broad-Coverage Semantic Parsing as Transduction
Sheng Zhang, Xutai Ma, Kevin Duh +1
We unify different broad-coverage semantic parsing tasks under a transduction paradigm, and propose an attention-based neural framework that incrementally builds a meaning represen…
A Call for Prudent Choice of Subword Merge Operations in Neural Machine Translation
Shuoyang Ding, Adithya Renduchintala, Kevin Duh
Most neural machine translation systems are built upon subword units extracted by methods such as Byte-Pair Encoding (BPE) or wordpiece. However, the choice of number of merge oper…
AMR Parsing as Sequence-to-Graph Transduction
Sheng Zhang, Xutai Ma, Kevin Duh +1
We propose an attention-based model that treats AMR parsing as sequence-to-graph transduction. Unlike most AMR parsers that rely on pre-trained aligners, external semantic resource…
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…
Query Expansion for Cross-Language Question Re-Ranking
Muhammad Mahbubur Rahman, Sorami Hisamoto, Kevin Duh
Community question-answering (CQA) platforms have become very popular forums for asking and answering questions daily. While these forums are rich repositories of community knowled…
Membership Inference Attacks on Sequence-to-Sequence Models: Is My Data In Your Machine Translation System?
Sorami Hisamoto, Matt Post, Kevin Duh
Data privacy is an important issue for "machine learning as a service" providers. We focus on the problem of membership inference attacks: given a data sample and black-box access…