Tobias Domhan

According to our database1, Tobias Domhan authored at least 14 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
A Shocking Amount of the Web is Machine Translated: Insights from Multi-Way Parallelism.
CoRR, 2024

2023
Trained MT Metrics Learn to Cope with Machine-translated References.
Proceedings of the Eighth Conference on Machine Translation, 2023

Findings of the WMT 2023 Shared Task on Parallel Data Curation.
Proceedings of the Eighth Conference on Machine Translation, 2023

2022
Sockeye 3: Fast Neural Machine Translation with PyTorch.
CoRR, 2022

The Devil is in the Details: On the Pitfalls of Vocabulary Selection in Neural Machine Translation.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

2021
Improving the Quality Trade-Off for Neural Machine Translation Multi-Domain Adaptation.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020
Sockeye 2: A Toolkit for Neural Machine Translation.
Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, 2020

The Sockeye 2 Neural Machine Translation Toolkit at AMTA 2020.
Proceedings of the 14th Conference of the Association for Machine Translation in the Americas, 2020

2018
Image Captioning as Neural Machine Translation Task in SOCKEYE.
CoRR, 2018

The Sockeye Neural Machine Translation Toolkit at AMTA 2018.
Proceedings of the 13th Conference of the Association for Machine Translation in the Americas, 2018

How Much Attention Do You Need? A Granular Analysis of Neural Machine Translation Architectures.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017
Sockeye: A Toolkit for Neural Machine Translation.
CoRR, 2017

Using Target-side Monolingual Data for Neural Machine Translation through Multi-task Learning.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

2015
Speeding Up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015


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