373 citations · 841 across the 71 of their papers we have counts for
10 papers · 1 filter
Gender Bias in Multilingual Neural Machine Translation: The Architecture Matters
Marta R. Costa-jussà, Carlos Escolano, Christine Basta +3
Multilingual Neural Machine Translation architectures mainly differ in the amount of sharing modules and parameters among languages. In this paper, and from an algorithmic perspect…
Continual Lifelong Learning in Natural Language Processing: A Survey
Magdalena Biesialska, Katarzyna Biesialska, Marta R. Costa-jussà
Continual learning (CL) aims to enable information systems to learn from a continuous data stream across time. However, it is difficult for existing deep learning architectures to…
Enabling Zero-shot Multilingual Spoken Language Translation with Language-Specific Encoders and Decoders
Carlos Escolano, Marta R. Costa-jussà, José A. R. Fonollosa +1
Current end-to-end approaches to Spoken Language Translation (SLT) rely on limited training resources, especially for multilingual settings. On the other hand, Multilingual Neural…
Evaluating Gender Bias in Speech Translation
Marta R. Costa-jussà, Christine Basta, Gerard I. Gállego
The scientific community is increasingly aware of the necessity to embrace pluralism and consistently represent major and minor social groups. Currently, there are no standard eval…
Training Multilingual Machine Translation by Alternately Freezing Language-Specific Encoders-Decoders
Carlos Escolano, Marta R. Costa-jussà, José A. R. Fonollosa +1
We propose a modular architecture of language-specific encoder-decoders that constitutes a multilingual machine translation system that can be incrementally extended to new languag…
MT-Adapted Datasheets for Datasets: Template and Repository
Marta R. Costa-jussà, Roger Creus, Oriol Domingo +5
In this report we are taking the standardized model proposed by Gebru et al. (2018) for documenting the popular machine translation datasets of the EuroParl (Koehn, 2005) and News-…
Enhancing Word Embeddings with Knowledge Extracted from Lexical Resources
Magdalena Biesialska, Bardia Rafieian, Marta R. Costa-jussà
In this work, we present an effective method for semantic specialization of word vector representations. To this end, we use traditional word embeddings and apply specialization me…
Multilingual Machine Translation: Closing the Gap between Shared and Language-specific Encoder-Decoders
Carlos Escolano, Marta R. Costa-jussà, José A. R. Fonollosa +1
State-of-the-art multilingual machine translation relies on a universal encoder-decoder, which requires retraining the entire system to add new languages. In this paper, we propose…
Syntax-driven Iterative Expansion Language Models for Controllable Text Generation
Noe Casas, José A. R. Fonollosa, Marta R. Costa-jussà
The dominant language modeling paradigm handles text as a sequence of discrete tokens. While that approach can capture the latent structure of the text, it is inherently constraine…
Refinement of Unsupervised Cross-Lingual Word Embeddings
Magdalena Biesialska, Marta R. Costa-jussà
Cross-lingual word embeddings aim to bridge the gap between high-resource and low-resource languages by allowing to learn multilingual word representations even without using any d…