Julia Kreutzer

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University of Heidelberg

Neural Machine Translation for Extremely Low-Resource African Languages: A Case Study on Bambara

Low-resource languages present unique challenges to (neural) machine tra...
11/10/2020 ∙ by Allahsera Auguste Tapo, et al. ∙ 6 ∙ share

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Learning from Human Feedback: Challenges for Real-World Reinforcement Learning in NLP

Large volumes of interaction logs can be collected from NLP systems that...
11/04/2020 ∙ by Julia Kreutzer, et al. ∙ 73 ∙ share

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KINNEWS and KIRNEWS: Benchmarking Cross-Lingual Text Classification for Kinyarwanda and Kirundi

Recent progress in text classification has been focused on high-resource...
10/23/2020 ∙ by Rubungo Andre Niyongabo, et al. ∙ 28 ∙ share

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Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages

Research in NLP lacks geographic diversity, and the question of how NLP ...
10/05/2020 ∙ by Wilhelmina Nekoto, et al. ∙ 0 ∙ share

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Inference Strategies for Machine Translation with Conditional Masking

Conditional masked language model (CMLM) training has proven successful ...
10/05/2020 ∙ by Julia Kreutzer, et al. ∙ 0 ∙ share

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Correct Me If You Can: Learning from Error Corrections and Markings

Sequence-to-sequence learning involves a trade-off between signal streng...
04/23/2020 ∙ by Julia Kreutzer, et al. ∙ 0 ∙ share

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On optimal transformer depth for low-resource language translation

Transformers have shown great promise as an approach to Neural Machine T...
04/09/2020 ∙ by Elan Van Biljon, et al. ∙ 0 ∙ share

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Masakhane – Machine Translation For Africa

Africa has over 2000 languages. Despite this, African languages account ...
03/13/2020 ∙ by Iroro Orife, et al. ∙ 0 ∙ share

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Joey NMT: A Minimalist NMT Toolkit for Novices

We present Joey NMT, a minimalist neural machine translation toolkit bas...
07/29/2019 ∙ by Julia Kreutzer, et al. ∙ 0 ∙ share

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Self-Regulated Interactive Sequence-to-Sequence Learning

Not all types of supervision signals are created equal: Different types ...
07/11/2019 ∙ by Julia Kreutzer, et al. ∙ 0 ∙ share

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Learning to Segment Inputs for NMT Favors Character-Level Processing

Most modern neural machine translation (NMT) systems rely on presegmente...
10/02/2018 ∙ by Julia Kreutzer, et al. ∙ 0 ∙ share

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Optimally Segmenting Inputs for NMT Shows Preference for Character-Level Processing

Most modern neural machine translation (NMT) systems rely on presegmente...
10/02/2018 ∙ by Julia Kreutzer, et al. ∙ 0 ∙ share

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Explaining and Generalizing Back-Translation through Wake-Sleep

Back-translation has become a commonly employed heuristic for semi-super...
06/12/2018 ∙ by Ryan Cotterell, et al. ∙ 0 ∙ share

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Reliability and Learnability of Human Bandit Feedback for Sequence-to-Sequence Reinforcement Learning

We present a study on reinforcement learning (RL) from human bandit feed...
05/27/2018 ∙ by Julia Kreutzer, et al. ∙ 0 ∙ share

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A Reinforcement Learning Approach to Interactive-Predictive Neural Machine Translation

We present an approach to interactive-predictive neural machine translat...
05/03/2018 ∙ by Tsz Kin Lam, et al. ∙ 0 ∙ share

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Can Neural Machine Translation be Improved with User Feedback?

We present the first real-world application of methods for improving neu...
04/16/2018 ∙ by Julia Kreutzer, et al. ∙ 0 ∙ share

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A Shared Task on Bandit Learning for Machine Translation

We introduce and describe the results of a novel shared task on bandit l...
07/27/2017 ∙ by Artem Sokolov, et al. ∙ 0 ∙ share

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Bandit Structured Prediction for Neural Sequence-to-Sequence Learning

Bandit structured prediction describes a stochastic optimization framewo...
04/21/2017 ∙ by Julia Kreutzer, et al. ∙ 0 ∙ share

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Stochastic Structured Prediction under Bandit Feedback

Stochastic structured prediction under bandit feedback follows a learnin...
06/02/2016 ∙ by Artem Sokolov, et al. ∙ 0 ∙ share

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Julia Kreutzer

Featured Co-authors

Ryan Cotterell

Herman Kamper

Marcos Zampieri

Stefan Riezler

Li Huang

Colin Cherry

George Foster

Shahram Khadivi

Vukosi Marivate

Artem Sokolov

Carolin Lawrence

Neural Machine Translation for Extremely Low-Resource African Languages: A Case Study on Bambara

Learning from Human Feedback: Challenges for Real-World Reinforcement Learning in NLP

KINNEWS and KIRNEWS: Benchmarking Cross-Lingual Text Classification for Kinyarwanda and Kirundi

Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages

Inference Strategies for Machine Translation with Conditional Masking

Correct Me If You Can: Learning from Error Corrections and Markings

On optimal transformer depth for low-resource language translation

Masakhane – Machine Translation For Africa

Joey NMT: A Minimalist NMT Toolkit for Novices

Self-Regulated Interactive Sequence-to-Sequence Learning

Learning to Segment Inputs for NMT Favors Character-Level Processing

Optimally Segmenting Inputs for NMT Shows Preference for Character-Level Processing

Explaining and Generalizing Back-Translation through Wake-Sleep

Reliability and Learnability of Human Bandit Feedback for Sequence-to-Sequence Reinforcement Learning

A Reinforcement Learning Approach to Interactive-Predictive Neural Machine Translation

Can Neural Machine Translation be Improved with User Feedback?

A Shared Task on Bandit Learning for Machine Translation

Bandit Structured Prediction for Neural Sequence-to-Sequence Learning

Stochastic Structured Prediction under Bandit Feedback