75 citations · 214 across the 27 of their papers we have counts for
6 papers · 1 filter
An Operation Sequence Model for Explainable Neural Machine Translation
Felix Stahlberg, Danielle Saunders, Bill Byrne
We propose to achieve explainable neural machine translation (NMT) by changing the output representation to explain itself. We present a novel approach to NMT which generates the t…
The University of Cambridge's Machine Translation Systems for WMT18
Felix Stahlberg, Adria de Gispert, Bill Byrne
The University of Cambridge submission to the WMT18 news translation task focuses on the combination of diverse models of translation. We compare recurrent, convolutional, and self…
Multi-representation Ensembles and Delayed SGD Updates Improve Syntax-based NMT
Danielle Saunders, Felix Stahlberg, Adria de Gispert +1
We explore strategies for incorporating target syntax into Neural Machine Translation. We specifically focus on syntax in ensembles containing multiple sentence representations. We…
Neural Machine Translation Decoding with Terminology Constraints
Eva Hasler, Adrià De Gispert, Gonzalo Iglesias +1
Despite the impressive quality improvements yielded by neural machine translation (NMT) systems, controlling their translation output to adhere to user-provided terminology constra…
Accelerating NMT Batched Beam Decoding with LMBR Posteriors for Deployment
Gonzalo Iglesias, William Tambellini, Adrià De Gispert +2
We describe a batched beam decoding algorithm for NMT with LMBR n-gram posteriors, showing that LMBR techniques still yield gains on top of the best recently reported results with…
Why not be Versatile? Applications of the SGNMT Decoder for Machine Translation
Felix Stahlberg, Danielle Saunders, Gonzalo Iglesias +1
SGNMT is a decoding platform for machine translation which allows paring various modern neural models of translation with different kinds of constraints and symbolic models. In thi…