Julia Kreutzer

research

∙ 11/04/2022

Intriguing Properties of Compression on Multilingual Models

Multilingual models are often particularly dependent on scaling to gener...

1 Kelechi Ogueji, et al. ∙

research

∙ 10/05/2022

JoeyS2T: Minimalistic Speech-to-Text Modeling with JoeyNMT

JoeyS2T is a JoeyNMT extension for speech-to-text tasks such as automati...

6 Mayumi Ohta, et al. ∙

research

∙ 05/09/2022

Building Machine Translation Systems for the Next Thousand Languages

In this paper we share findings from our effort to build practical machi...

8 Ankur Bapna, et al. ∙

research

∙ 12/16/2021

Can Multilinguality benefit Non-autoregressive Machine Translation?

Non-autoregressive (NAR) machine translation has recently achieved signi...

4 Sweta Agrawal, et al. ∙

research

∙ 10/13/2021

Bandits Don't Follow Rules: Balancing Multi-Facet Machine Translation with Multi-Armed Bandits

Training data for machine translation (MT) is often sourced from a multi...

8 Julia Kreutzer, et al. ∙

research

∙ 10/06/2021

The Low-Resource Double Bind: An Empirical Study of Pruning for Low-Resource Machine Translation

A "bigger is better" explosion in the number of parameters in deep neura...

52 Orevaoghene Ahia, et al. ∙

research

∙ 09/13/2021

Evaluating Multiway Multilingual NMT in the Turkic Languages

Despite the increasing number of large and comprehensive machine transla...

11 Jamshidbek Mirzakhalov, et al. ∙

research

∙ 07/23/2021

Modelling Latent Translations for Cross-Lingual Transfer

While achieving state-of-the-art results in multiple tasks and languages...

7 Edoardo Maria Ponti, et al. ∙

research

∙ 06/16/2021

Revisiting the Weaknesses of Reinforcement Learning for Neural Machine Translation

Policy gradient algorithms have found wide adoption in NLP, but have rec...

15 Samuel Kiegeland, et al. ∙

research

∙ 03/22/2021

Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets

With the success of large-scale pre-training and multilingual modeling i...

33 Isaac Caswell, et al. ∙

research

∙ 03/22/2021

MasakhaNER: Named Entity Recognition for African Languages

We take a step towards addressing the under-representation of the Africa...

5 David Ifeoluwa Adelani, et al. ∙

research

∙ 11/10/2020

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

Low-resource languages present unique challenges to (neural) machine tra...

6 Allahsera Auguste Tapo, et al. ∙

research

∙ 11/04/2020

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

Large volumes of interaction logs can be collected from NLP systems that...

73 Julia Kreutzer, et al. ∙

research

∙ 10/23/2020

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

Recent progress in text classification has been focused on high-resource...

28 Rubungo Andre Niyongabo, et al. ∙

research

∙ 10/05/2020

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 ...

0 Wilhelmina Nekoto, et al. ∙

research

∙ 10/05/2020

Inference Strategies for Machine Translation with Conditional Masking

Conditional masked language model (CMLM) training has proven successful ...

0 Julia Kreutzer, et al. ∙

research

∙ 04/23/2020

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

Sequence-to-sequence learning involves a trade-off between signal streng...

0 Julia Kreutzer, et al. ∙

research

∙ 04/09/2020

On optimal transformer depth for low-resource language translation

Transformers have shown great promise as an approach to Neural Machine T...

0 Elan Van Biljon, et al. ∙

research

∙ 03/13/2020

Masakhane – Machine Translation For Africa

Africa has over 2000 languages. Despite this, African languages account ...

0 Iroro Orife, et al. ∙

research

∙ 07/29/2019

Joey NMT: A Minimalist NMT Toolkit for Novices

We present Joey NMT, a minimalist neural machine translation toolkit bas...

0 Julia Kreutzer, et al. ∙

research

∙ 07/11/2019

Self-Regulated Interactive Sequence-to-Sequence Learning

Not all types of supervision signals are created equal: Different types ...

0 Julia Kreutzer, et al. ∙

research

∙ 10/02/2018

Learning to Segment Inputs for NMT Favors Character-Level Processing

Most modern neural machine translation (NMT) systems rely on presegmente...

0 Julia Kreutzer, et al. ∙

research

∙ 10/02/2018

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

Most modern neural machine translation (NMT) systems rely on presegmente...

0 Julia Kreutzer, et al. ∙

research

∙ 06/12/2018

Explaining and Generalizing Back-Translation through Wake-Sleep

Back-translation has become a commonly employed heuristic for semi-super...

0 Ryan Cotterell, et al. ∙

research

∙ 05/27/2018

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...

0 Julia Kreutzer, et al. ∙

research

∙ 05/03/2018

A Reinforcement Learning Approach to Interactive-Predictive Neural Machine Translation

We present an approach to interactive-predictive neural machine translat...

0 Tsz Kin Lam, et al. ∙

research

∙ 04/16/2018

Can Neural Machine Translation be Improved with User Feedback?

We present the first real-world application of methods for improving neu...

0 Julia Kreutzer, et al. ∙

research

∙ 07/27/2017

A Shared Task on Bandit Learning for Machine Translation

We introduce and describe the results of a novel shared task on bandit l...

0 Artem Sokolov, et al. ∙

research

∙ 04/21/2017

Bandit Structured Prediction for Neural Sequence-to-Sequence Learning

Bandit structured prediction describes a stochastic optimization framewo...

0 Julia Kreutzer, et al. ∙

research

∙ 06/02/2016

Stochastic Structured Prediction under Bandit Feedback

Stochastic structured prediction under bandit feedback follows a learnin...

0 Artem Sokolov, et al. ∙

Julia Kreutzer

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