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09/20/2023
Towards Effective Disambiguation for Machine Translation with Large Language Models
Resolving semantic ambiguity has long been recognised as a central chall...
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05/23/2023
When Does Monolingual Data Help Multilingual Translation: The Role of Domain and Model Scale
Multilingual machine translation (MMT), trained on a mixture of parallel...
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03/28/2023
Hallucinations in Large Multilingual Translation Models
Large-scale multilingual machine translation systems have demonstrated r...
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01/17/2023
Prompting Large Language Model for Machine Translation: A Case Study
Research on prompting has shown excellent performance with little or eve...
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12/20/2022
MULTI3NLU++: A Multilingual, Multi-Intent, Multi-Domain Dataset for Natural Language Understanding in Task-Oriented Dialogue
Task-oriented dialogue (TOD) systems have been applied in a range of dom...
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12/20/2022
Extrinsic Evaluation of Machine Translation Metrics
Automatic machine translation (MT) metrics are widely used to distinguis...
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06/01/2022
Exploring Diversity in Back Translation for Low-Resource Machine Translation
Back translation is one of the most widely used methods for improving th...
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05/06/2022
Quantifying Synthesis and Fusion and their Impact on Machine Translation
Theoretical work in morphological typology offers the possibility of mea...
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05/04/2022
Non-Autoregressive Machine Translation: It's Not as Fast as it Seems
Efficient machine translation models are commercially important as they ...
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10/25/2021
Distributionally Robust Recurrent Decoders with Random Network Distillation
Neural machine learning models can successfully model language that is s...
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09/28/2021
Cross-lingual Intermediate Fine-tuning improves Dialogue State Tracking
Recent progress in task-oriented neural dialogue systems is largely focu...
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09/10/2021
CoPHE: A Count-Preserving Hierarchical Evaluation Metric in Large-Scale Multi-Label Text Classification
Large-Scale Multi-Label Text Classification (LMTC) includes tasks with h...
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09/01/2021
Survey of Low-Resource Machine Translation
We present a survey covering the state of the art in low-resource machin...
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06/10/2021
Exploring Unsupervised Pretraining Objectives for Machine Translation
Unsupervised cross-lingual pretraining has achieved strong results in ne...
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03/31/2021
Few-shot learning through contextual data augmentation
Machine translation (MT) models used in industries with constantly chang...
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04/30/2020
Language Model Prior for Low-Resource Neural Machine Translation
The scarcity of large parallel corpora is an important obstacle for neur...
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04/30/2020
Bridging linguistic typology and multilingual machine translation with multi-view language representations
Sparse language vectors from linguistic typology databases and learned e...
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02/19/2020
Toward Making the Most of Context in Neural Machine Translation
Document-level machine translation manages to outperform sentence level ...
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10/30/2019
A Latent Morphology Model for Open-Vocabulary Neural Machine Translation
Translation into morphologically-rich languages challenges neural machin...
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10/29/2019
Findings of the Third Workshop on Neural Generation and Translation
This document describes the findings of the Third Workshop on Neural Gen...
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10/15/2019
On the Importance of Word Boundaries in Character-level Neural Machine Translation
Neural Machine Translation (NMT) models generally perform translation us...
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07/12/2019
The University of Edinburgh's Submissions to the WMT19 News Translation Task
The University of Edinburgh participated in the WMT19 Shared Task on New...
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09/02/2018
Exploring Gap Filling as a Cheaper Alternative to Reading Comprehension Questionnaires when Evaluating Machine Translation for Gisting
A popular application of machine translation (MT) is gisting: MT is cons...
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06/08/2018
Findings of the Second Workshop on Neural Machine Translation and Generation
This document describes the findings of the Second Workshop on Neural Ma...
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04/01/2018
Marian: Fast Neural Machine Translation in C++
We present Marian, an efficient and self-contained Neural Machine Transl...
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11/01/2017
Evaluating Discourse Phenomena in Neural Machine Translation
For machine translation to tackle discourse phenomena, models must have ...
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08/02/2017
The University of Edinburgh's Neural MT Systems for WMT17
This paper describes the University of Edinburgh's submissions to the WM...
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07/24/2017
Deep Architectures for Neural Machine Translation
It has been shown that increasing model depth improves the quality of ne...
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03/13/2017
Nematus: a Toolkit for Neural Machine Translation
We present Nematus, a toolkit for Neural Machine Translation. The toolki...
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02/03/2017
Predicting Target Language CCG Supertags Improves Neural Machine Translation
Neural machine translation (NMT) models are able to partially learn synt...
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06/30/2016
HUME: Human UCCA-Based Evaluation of Machine Translation
Human evaluation of machine translation normally uses sentence-level mea...
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06/09/2016
Edinburgh Neural Machine Translation Systems for WMT 16
We participated in the WMT 2016 shared news translation task by building...
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11/20/2015
Improving Neural Machine Translation Models with Monolingual Data
Neural Machine Translation (NMT) has obtained state-of-the art performan...
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08/31/2015
