David Grangier

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Research Scientist at Facebook

Contrastive Learning of General-Purpose Audio Representations

We introduce COLA, a self-supervised pre-training approach for learning ...
10/21/2020 ∙ by Aaqib Saeed, et al. ∙ 6 ∙ share

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Human-Paraphrased References Improve Neural Machine Translation

Automatic evaluation comparing candidate translations to human-generated...
10/20/2020 ∙ by Markus Freitag, et al. ∙ 0 ∙ share

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Toward Better Storylines with Sentence-Level Language Models

We propose a sentence-level language model which selects the next senten...
05/11/2020 ∙ by Daphne Ippolito, et al. ∙ 0 ∙ share

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BLEU might be Guilty but References are not Innocent

The quality of automatic metrics for machine translation has been increa...
04/13/2020 ∙ by Markus Freitag, et al. ∙ 0 ∙ share

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Efficient Content-Based Sparse Attention with Routing Transformers

Self-attention has recently been adopted for a wide range of sequence mo...
03/12/2020 ∙ by Aurko Roy, et al. ∙ 3 ∙ share

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Wavesplit: End-to-End Speech Separation by Speaker Clustering

We introduce Wavesplit, an end-to-end speech separation system. From a s...
02/20/2020 ∙ by Neil Zeghidour, et al. ∙ 37 ∙ share

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Translationese as a Language in "Multilingual" NMT

Machine translation has an undesirable propensity to produce "translatio...
11/10/2019 ∙ by Parker Riley, et al. ∙ 0 ∙ share

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ELI5: Long Form Question Answering

We introduce the first large-scale corpus for long-form question answeri...
07/22/2019 ∙ by Angela Fan, et al. ∙ 0 ∙ share

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Tagged Back-Translation

Recent work in Neural Machine Translation (NMT) has shown significant qu...
06/15/2019 ∙ by Isaac Caswell, et al. ∙ 0 ∙ share

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Unsupervised Paraphrasing without Translation

Paraphrasing exemplifies the ability to abstract semantic content from s...
05/29/2019 ∙ by Aurko Roy, et al. ∙ 0 ∙ share

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fairseq: A Fast, Extensible Toolkit for Sequence Modeling

fairseq is an open-source sequence modeling toolkit that allows research...
04/01/2019 ∙ by Myle Ott, et al. ∙ 0 ∙ share

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Modeling Human Motion with Quaternion-based Neural Networks

Previous work on predicting or generating 3D human pose sequences regres...
01/21/2019 ∙ by Dario Pavllo, et al. ∙ 0 ∙ share

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3D human pose estimation in video with temporal convolutions and semi-supervised training

In this work, we demonstrate that 3D poses in video can be effectively e...
11/28/2018 ∙ by Dario Pavllo, et al. ∙ 0 ∙ share

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Understanding Back-Translation at Scale

An effective method to improve neural machine translation with monolingu...
08/28/2018 ∙ by Sergey Edunov, et al. ∙ 0 ∙ share

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Scaling Neural Machine Translation

Sequence to sequence learning models still require several days to reach...
06/01/2018 ∙ by Myle Ott, et al. ∙ 0 ∙ share

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QuaterNet: A Quaternion-based Recurrent Model for Human Motion

Deep learning for predicting or generating 3D human pose sequences is an...
05/16/2018 ∙ by Dario Pavllo, et al. ∙ 0 ∙ share

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Controllable Abstractive Summarization

Current models for document summarization ignore user preferences such a...
11/14/2017 ∙ by Angela Fan, et al. ∙ 0 ∙ share

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Classical Structured Prediction Losses for Sequence to Sequence Learning

There has been much recent work on training neural attention models at t...
11/14/2017 ∙ by Sergey Edunov, et al. ∙ 0 ∙ share

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QuickEdit: Editing Text & Translations via Simple Delete Actions

We propose a framework for computer-assisted text editing. It applies to...
11/13/2017 ∙ by David Grangier, et al. ∙ 0 ∙ share

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Convolutional Sequence to Sequence Learning

The prevalent approach to sequence to sequence learning maps an input se...
05/08/2017 ∙ by Jonas Gehring, et al. ∙ 0 ∙ share

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Language Modeling with Gated Convolutional Networks

The pre-dominant approach to language modeling to date is based on recur...
12/23/2016 ∙ by Yann N. Dauphin, et al. ∙ 0 ∙ share

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A Convolutional Encoder Model for Neural Machine Translation

The prevalent approach to neural machine translation relies on bi-direct...
11/07/2016 ∙ by Jonas Gehring, et al. ∙ 0 ∙ share

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Iterative Refinement for Machine Translation

Existing machine translation decoding algorithms generate translations i...
10/20/2016 ∙ by Roman Novak, et al. ∙ 0 ∙ share

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Vocabulary Selection Strategies for Neural Machine Translation

Classical translation models constrain the space of possible outputs by ...
10/01/2016 ∙ by Gurvan L'Hostis, et al. ∙ 0 ∙ share

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Efficient softmax approximation for GPUs

We propose an approximate strategy to efficiently train neural network b...
09/14/2016 ∙ by Edouard Grave, et al. ∙ 0 ∙ share

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Interactive Semantic Featuring for Text Classification

In text classification, dictionaries can be used to define human-compreh...
06/24/2016 ∙ by Camille Jandot, et al. ∙ 0 ∙ share

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Neural Text Generation from Structured Data with Application to the Biography Domain

This paper introduces a neural model for concept-to-text generation that...
03/24/2016 ∙ by Rémi Lebret, et al. ∙ 0 ∙ share

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Strategies for Training Large Vocabulary Neural Language Models

Training neural network language models over large vocabularies is still...
12/15/2015 ∙ by Welin Chen, et al. ∙ 0 ∙ share

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ICE: Enabling Non-Experts to Build Models Interactively for Large-Scale Lopsided Problems

Quick interaction between a human teacher and a learning machine present...
09/16/2014 ∙ by Patrice Simard, et al. ∙ 0 ∙ share

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David Grangier

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