1 citations · 2 across the 4 of their papers we have counts for
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From Rewriting to Remembering: Common Ground for Conversational QA Models
Marco Del Tredici, Xiaoyu Shen, Gianni Barlacchi +2
In conversational QA, models have to leverage information in previous turns to answer upcoming questions. Current approaches, such as Question Rewriting, struggle to extract releva…
Cued@wmt19:ewc&lms
Felix Stahlberg, Danielle Saunders, Adria de Gispert +1
Two techniques provide the fabric of the Cambridge University Engineering Department's (CUED) entry to the WMT19 evaluation campaign: elastic weight consolidation (EWC) and differe…
Domain Adaptive Inference for Neural Machine Translation
Danielle Saunders, Felix Stahlberg, Adria de Gispert +1
We investigate adaptive ensemble weighting for Neural Machine Translation, addressing the case of improving performance on a new and potentially unknown domain without sacrificing…
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…