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05/19/2023
XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages
Data scarcity is a crucial issue for the development of highly multiling...
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02/02/2023
The unreasonable effectiveness of few-shot learning for machine translation
We demonstrate the potential of few-shot translation systems, trained wi...
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12/19/2022
Mu^2SLAM: Multitask, Multilingual Speech and Language Models
We present Mu^2SLAM, a multilingual sequence-to-sequence model pre-train...
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03/21/2022
XTREME-S: Evaluating Cross-lingual Speech Representations
We introduce XTREME-S, a new benchmark to evaluate universal cross-lingu...
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02/03/2022
mSLAM: Massively multilingual joint pre-training for speech and text
We present mSLAM, a multilingual Speech and LAnguage Model that learns c...
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12/16/2021
DOCmT5: Document-Level Pretraining of Multilingual Language Models
In this paper, we introduce DOCmT5, a multilingual sequence-to-sequence ...
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10/20/2021
SLAM: A Unified Encoder for Speech and Language Modeling via Speech-Text Joint Pre-Training
Unsupervised pre-training is now the predominant approach for both text ...
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09/21/2021
Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents
Document-level neural machine translation (DocNMT) delivers coherent tra...
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09/09/2021
HintedBT: Augmenting Back-Translation with Quality and Transliteration Hints
Back-translation (BT) of target monolingual corpora is a widely used dat...
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06/05/2021
MergeDistill: Merging Pre-trained Language Models using Distillation
Pre-trained multilingual language models (LMs) have achieved state-of-th...
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06/03/2021
nmT5 – Is parallel data still relevant for pre-training massively multilingual language models?
Recently, mT5 - a massively multilingual version of T5 - leveraged a uni...
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04/15/2021
XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation
Machine learning has brought striking advances in multilingual natural l...
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02/26/2021
Gradient-guided Loss Masking for Neural Machine Translation
To mitigate the negative effect of low quality training data on the perf...
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02/12/2021
They, Them, Theirs: Rewriting with Gender-Neutral English
Responsible development of technology involves applications being inclus...
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01/21/2021
Distilling Large Language Models into Tiny and Effective Students using pQRNN
Large pre-trained multilingual models like mBERT, XLM-R achieve state of...
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10/24/2020
Rethinking embedding coupling in pre-trained language models
We re-evaluate the standard practice of sharing weights between input an...
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10/15/2020
Explicit Alignment Objectives for Multilingual Bidirectional Encoders
Pre-trained cross-lingual encoders such as mBERT (Devlin et al., 2019) a...
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03/24/2020
XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization
Much recent progress in applications of machine learning models to NLP h...
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09/13/2019
Adaptive Scheduling for Multi-Task Learning
To train neural machine translation models simultaneously on multiple ta...
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09/01/2019
Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation
The recently proposed massively multilingual neural machine translation ...
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08/31/2019
Small and Practical BERT Models for Sequence Labeling
We propose a practical scheme to train a single multilingual sequence la...
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07/11/2019
Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges
We introduce our efforts towards building a universal neural machine tra...
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04/12/2019
Direct speech-to-speech translation with a sequence-to-sequence model
We present an attention-based sequence-to-sequence neural network which ...
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03/17/2019
The Missing Ingredient in Zero-Shot Neural Machine Translation
Multilingual Neural Machine Translation (NMT) models are capable of tran...
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02/28/2019
Massively Multilingual Neural Machine Translation
Multilingual neural machine translation (NMT) enables training a single ...
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02/21/2019
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
Lingvo is a Tensorflow framework offering a complete solution for collab...
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11/05/2018
Leveraging Weakly Supervised Data to Improve End-to-End Speech-to-Text Translation
End-to-end Speech Translation (ST) models have many potential advantages...
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09/12/2018
Zero-Shot Cross-lingual Classification Using Multilingual Neural Machine Translation
Transferring representations from large supervised tasks to downstream t...
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04/26/2018
The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation
The past year has witnessed rapid advances in sequence-to-sequence (seq2...
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11/14/2016
Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation
We propose a simple solution to use a single Neural Machine Translation ...
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09/26/2016
