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Alexandre Muzio

3 accepted papers

2022

Gating Dropout: Communication-efficient Regularization for Sparsely Activated Transformers

ICML 2022spotlight

Sparsely activated transformers, such as Mixture of Experts (MoE), have received great interest due to their outrageous scaling capability which enables dramatical increases in model size without significant increases in computational cost. To achieve this, MoE models replace the feedforward sub-lay…

2021

Discovering Representation Sprachbund For Multilingual Pre-Training

EMNLP 2021finding

Multilingual pre-trained models have demonstrated their effectiveness in many multilingual NLP tasks and enabled zero-shot or few-shot transfer from high-resource languages to low-resource ones. However, due to significant typological differences and contradictions between some languages, such model…

2021

Improving Multilingual Translation by Representation and Gradient Regularization

EMNLP 2021main

Multilingual Neural Machine Translation (NMT) enables one model to serve all translation directions, including ones that are unseen during training, i.e. zero-shot translation. Despite being theoretically attractive, current models often produce low quality translations – commonly failing to even pr…