David Grangier

ORCID

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 81

Top Venues

CoRR

ACL (1)

ICML

Trans. Assoc. Comput. Linguistics

Publications

Pratyush Maini, Skyler Seto, He Bai, David Grangier, Yizhe Zhang, Navdeep Jaitly
Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling. CoRR (2024)
Pratyush Maini, Skyler Seto, Richard He Bai, David Grangier, Yizhe Zhang, Navdeep Jaitly
Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling. ACL (1) (2024)
David Grangier, Angelos Katharopoulos, Pierre Ablin, Awni Hannun
Specialized Language Models with Cheap Inference from Limited Domain Data. CoRR (2024)
Zalán Borsos, Raphaël Marinier, Damien Vincent, Eugene Kharitonov, Olivier Pietquin, Matthew Sharifi, Dominik Roblek, Olivier Teboul, David Grangier, Marco Tagliasacchi, Neil Zeghidour
AudioLM: A Language Modeling Approach to Audio Generation. IEEE ACM Trans. Audio Speech Lang. Process. 31 (2023)
David Grangier, Pierre Ablin, Awni Hannun
Adaptive Training Distributions with Scalable Online Bilevel Optimization. CoRR (2023)
Lucio M. Dery, David Grangier, Awni Hannun
Transfer Learning for Structured Pruning under Limited Task Data. CoRR (2023)
Rachid Riad, Olivier Teboul, David Grangier, Neil Zeghidour
Learning strides in convolutional neural networks. CoRR (2022)
Markus Freitag, David Grangier, Qijun Tan, Bowen Liang
High Quality Rather than High Model Probability: Minimum Bayes Risk Decoding with Neural Metrics. Trans. Assoc. Comput. Linguistics 10 (2022)
Kelly Marchisio, Markus Freitag, David Grangier
On Systematic Style Differences between Unsupervised and Supervised MT and an Application for High-Resource Machine Translation. NAACL-HLT (2022)
Maartje ter Hoeve, David Grangier, Natalie Schluter
High-Resource Methodological Bias in Low-Resource Investigations. CoRR (2022)
Rachid Riad, Olivier Teboul, David Grangier, Neil Zeghidour
Learning Strides in Convolutional Neural Networks. ICLR (2022)
Markus Freitag, David Vilar, David Grangier, Colin Cherry, George F. Foster
A Natural Diet: Towards Improving Naturalness of Machine Translation Output. ACL (Findings) (2022)
Zalán Borsos, Raphaël Marinier, Damien Vincent, Eugene Kharitonov, Olivier Pietquin, Matthew Sharifi, Olivier Teboul, David Grangier, Marco Tagliasacchi, Neil Zeghidour
AudioLM: a Language Modeling Approach to Audio Generation. CoRR (2022)
David Grangier, Dan Iter
The Trade-offs of Domain Adaptation for Neural Language Models. ACL (1) (2022)
Neil Zeghidour, Olivier Teboul, David Grangier
DIVE: End-to-end Speech Diarization via Iterative Speaker Embedding. CoRR (2021)
Lucio M. Dery, Yann N. Dauphin, David Grangier
Auxiliary Task Update Decomposition: The Good, The Bad and The Neutral. CoRR (2021)
Aaqib Saeed, David Grangier, Olivier Pietquin, Neil Zeghidour
Learning From Heterogeneous Eeg Signals with Differentiable Channel Reordering. ICASSP (2021)
Markus Freitag, George F. Foster, David Grangier, Viresh Ratnakar, Qijun Tan, Wolfgang Macherey
Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation. Trans. Assoc. Comput. Linguistics 9 (2021)
Kelly Marchisio, Markus Freitag, David Grangier
What Can Unsupervised Machine Translation Contribute to High-Resource Language Pairs? CoRR (2021)
Neil Zeghidour, Olivier Teboul, David Grangier
Dive: End-to-End Speech Diarization Via Iterative Speaker Embedding. ASRU (2021)
Neil Zeghidour, David Grangier
Wavesplit: End-to-End Speech Separation by Speaker Clustering. IEEE ACM Trans. Audio Speech Lang. Process. 29 (2021)
Dan Iter, David Grangier
On the Complementarity of Data Selection and Fine Tuning for Domain Adaptation. CoRR (2021)
Dan Iter, David Grangier
The Trade-offs of Domain Adaptation for Neural Language Models. CoRR (2021)
Lucio M. Dery, Yann N. Dauphin, David Grangier
Auxiliary Task Update Decomposition: the Good, the Bad and the neutral. ICLR (2021)
Aaqib Saeed, David Grangier, Neil Zeghidour
Contrastive Learning of General-Purpose Audio Representations. ICASSP (2021)
Markus Freitag, George F. Foster, David Grangier, Viresh Ratnakar, Qijun Tan, Wolfgang Macherey
Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation. CoRR (2021)
Aurko Roy, Mohammad Saffar, Ashish Vaswani, David Grangier
Efficient Content-Based Sparse Attention with Routing Transformers. Trans. Assoc. Comput. Linguistics 9 (2021)
Markus Freitag, David Grangier, Qijun Tan, Bowen Liang
Minimum Bayes Risk Decoding with Neural Metrics of Translation Quality. CoRR (2021)
Markus Freitag, David Grangier, Isaac Caswell
BLEU might be Guilty but References are not Innocent. CoRR (2020)
Aaqib Saeed, David Grangier, Neil Zeghidour
Contrastive Learning of General-Purpose Audio Representations. CoRR (2020)
Markus Freitag, David Grangier, Isaac Caswell
BLEU might be Guilty but References are not Innocent. EMNLP (1) (2020)
Aaqib Saeed, David Grangier, Olivier Pietquin, Neil Zeghidour
Learning from Heterogeneous EEG Signals with Differentiable Channel Reordering. CoRR (2020)
Daphne Ippolito, David Grangier, Douglas Eck, Chris Callison-Burch
Toward Better Storylines with Sentence-Level Language Models. CoRR (2020)
Neil Zeghidour, David Grangier
Wavesplit: End-to-End Speech Separation by Speaker Clustering. CoRR (2020)
Markus Freitag, George F. Foster, David Grangier, Colin Cherry
Human-Paraphrased References Improve Neural Machine Translation. WMT@EMNLP (2020)
Dario Pavllo, Christoph Feichtenhofer, Michael Auli, David Grangier
Modeling Human Motion with Quaternion-Based Neural Networks. Int. J. Comput. Vis. 128 (4) (2020)
Parker Riley, Isaac Caswell, Markus Freitag, David Grangier
Translationese as a Language in "Multilingual" NMT. ACL (2020)
Markus Freitag, George F. Foster, David Grangier, Colin Cherry
Human-Paraphrased References Improve Neural Machine Translation. CoRR (2020)
Aurko Roy, Mohammad Saffar, Ashish Vaswani, David Grangier
Efficient Content-Based Sparse Attention with Routing Transformers. CoRR (2020)
Daphne Ippolito, David Grangier, Douglas Eck, Chris Callison-Burch
Toward Better Storylines with Sentence-Level Language Models. ACL (2020)
Aurko Roy, David Grangier
Unsupervised Paraphrasing without Translation. ACL (1) (2019)
Isaac Caswell, Ciprian Chelba, David Grangier
Tagged Back-Translation. CoRR (2019)
Dario Pavllo, Christoph Feichtenhofer, David Grangier, Michael Auli
3D Human Pose Estimation in Video With Temporal Convolutions and Semi-Supervised Training. CVPR (2019)
Angela Fan, Yacine Jernite, Ethan Perez, David Grangier, Jason Weston, Michael Auli
ELI5: Long Form Question Answering. ACL (1) (2019)
Angela Fan, Yacine Jernite, Ethan Perez, David Grangier, Jason Weston, Michael Auli
ELI5: Long Form Question Answering. CoRR (2019)
Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, Michael Auli
fairseq: A Fast, Extensible Toolkit for Sequence Modeling. NAACL-HLT (Demonstrations) (2019)
Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, Michael Auli
fairseq: A Fast, Extensible Toolkit for Sequence Modeling. CoRR (2019)
Isaac Caswell, Ciprian Chelba, David Grangier
Tagged Back-Translation. WMT (1) (2019)
Parker Riley, Isaac Caswell, Markus Freitag, David Grangier
Translationese as a Language in "Multilingual" NMT. CoRR (2019)
Aurko Roy, David Grangier
Unsupervised Paraphrasing without Translation. CoRR (2019)
Dario Pavllo, Christoph Feichtenhofer, Michael Auli, David Grangier
Modeling Human Motion with Quaternion-based Neural Networks. CoRR (2019)
Dario Pavllo, Christoph Feichtenhofer, David Grangier, Michael Auli
3D human pose estimation in video with temporal convolutions and semi-supervised training. CoRR (2018)
Dario Pavllo, David Grangier, Michael Auli
QuaterNet: A Quaternion-based Recurrent Model for Human Motion. CoRR (2018)
Angela Fan, David Grangier, Michael Auli
Controllable Abstractive Summarization. NMT@ACL (2018)
David Grangier, Michael Auli
QuickEdit: Editing Text & Translations by Crossing Words Out. NAACL-HLT (2018)
Myle Ott, Sergey Edunov, David Grangier, Michael Auli
Scaling Neural Machine Translation. CoRR (2018)
Sergey Edunov, Myle Ott, Michael Auli, David Grangier
Understanding Back-Translation at Scale. EMNLP (2018)
Myle Ott, Michael Auli, David Grangier, Marc'Aurelio Ranzato
Analyzing Uncertainty in Neural Machine Translation. ICML (2018)
Sergey Edunov, Myle Ott, Michael Auli, David Grangier
Understanding Back-Translation at Scale. CoRR (2018)
Myle Ott, Michael Auli, David Grangier, Marc'Aurelio Ranzato
Analyzing Uncertainty in Neural Machine Translation. CoRR (2018)
Dario Pavllo, David Grangier, Michael Auli
QuaterNet: A Quaternion-based Recurrent Model for Human Motion. BMVC (2018)
Myle Ott, Sergey Edunov, David Grangier, Michael Auli
Scaling Neural Machine Translation. WMT (2018)
Sergey Edunov, Myle Ott, Michael Auli, David Grangier, Marc'Aurelio Ranzato
Classical Structured Prediction Losses for Sequence to Sequence Learning. NAACL-HLT (2018)
Angela Fan, David Grangier, Michael Auli
Controllable Abstractive Summarization. CoRR (2017)
Jonas Gehring, Michael Auli, David Grangier, Yann N. Dauphin
A Convolutional Encoder Model for Neural Machine Translation. ACL (1) (2017)
David Grangier, Michael Auli
QuickEdit: Editing Text & Translations via Simple Delete Actions. CoRR (2017)
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin
Convolutional Sequence to Sequence Learning. CoRR (2017)
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin
Convolutional Sequence to Sequence Learning. ICML (2017)
Edouard Grave, Armand Joulin, Moustapha Cissé, David Grangier, Hervé Jégou
Efficient softmax approximation for GPUs. ICML (2017)
Yann N. Dauphin, Angela Fan, Michael Auli, David Grangier
Language Modeling with Gated Convolutional Networks. ICML (2017)
Sergey Edunov, Myle Ott, Michael Auli, David Grangier, Marc'Aurelio Ranzato
Classical Structured Prediction Losses for Sequence to Sequence Learning. CoRR (2017)
Yann N. Dauphin, David Grangier
Predicting distributions with Linearizing Belief Networks. ICLR (Poster) (2016)
Rémi Lebret, David Grangier, Michael Auli
Generating Text from Structured Data with Application to the Biography Domain. CoRR (2016)
Yann N. Dauphin, Angela Fan, Michael Auli, David Grangier
Language Modeling with Gated Convolutional Networks. CoRR (2016)
Wenlin Chen, David Grangier, Michael Auli
Strategies for Training Large Vocabulary Neural Language Models. ACL (1) (2016)
Rémi Lebret, David Grangier, Michael Auli
Neural Text Generation from Structured Data with Application to the Biography Domain. EMNLP (2016)
Camille Jandot, Patrice Y. Simard, Max Chickering, David Grangier, Jina Suh
Interactive Semantic Featuring for Text Classification. CoRR (2016)
Edouard Grave, Armand Joulin, Moustapha Cissé, David Grangier, Hervé Jégou
Efficient softmax approximation for GPUs. CoRR (2016)
Gurvan L'Hostis, David Grangier, Michael Auli
Vocabulary Selection Strategies for Neural Machine Translation. CoRR (2016)
Jonas Gehring, Michael Auli, David Grangier, Yann N. Dauphin
A Convolutional Encoder Model for Neural Machine Translation. CoRR (2016)
Roman Novak, Michael Auli, David Grangier
Iterative Refinement for Machine Translation. CoRR (2016)
Wenlin Chen, David Grangier, Michael Auli
Strategies for Training Large Vocabulary Neural Language Models. CoRR (2015)
Xiaoxiao Shi, Jean-François Paiement, David Grangier, Philip S. Yu
GBC: Gradient boosting consensus model for heterogeneous data. Stat. Anal. Data Min. 7 (3) (2014)
Patrice Y. Simard, David Maxwell Chickering, Aparna Lakshmiratan, Denis Xavier Charles, Léon Bottou, Carlos Garcia Jurado Suarez, David Grangier, Saleema Amershi, Johan Verwey, Jina Suh
ICE: Enabling Non-Experts to Build Models Interactively for Large-Scale Lopsided Problems. CoRR (2014)
Xiaoxiao Shi, Jean-François Paiement, David Grangier, Philip S. Yu
Learning from Heterogeneous Sources via Gradient Boosting Consensus. SDM (2012)
Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Corinna Cortes, Mehryar Mohri
Half Transductive Ranking. AISTATS (2010)
Samy Bengio, Jason Weston, David Grangier
Label Embedding Trees for Large Multi-Class Tasks. NIPS (2010)
David Grangier, Iain Melvin
Feature Set Embedding for Incomplete Data. NIPS (2010)
Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Olivier Chapelle, Kilian Q. Weinberger
Learning to rank with (a lot of) word features. Inf. Retr. 13 (3) (2010)
Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Olivier Chapelle, Kilian Q. Weinberger
Supervised semantic indexing. CIKM (2009)
Bing Bai, Jason Weston, Ronan Collobert, David Grangier
Supervised Semantic Indexing. ECIR (2009)
Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Corinna Cortes, Mehryar Mohri
Polynomial Semantic Indexing. NIPS (2009)
Joseph Keshet, David Grangier, Samy Bengio
Discriminative keyword spotting. Speech Commun. 51 (4) (2009)
David Grangier, Samy Bengio
A Discriminative Kernel-Based Approach to Rank Images from Text Queries. IEEE Trans. Pattern Anal. Mach. Intell. 30 (8) (2008)
David Grangier, Samy Bengio
Learning the inter-frame distance for discriminative template-based keyword detection. INTERSPEECH (2007)
David Grangier, Florent Monay, Samy Bengio
A Discriminative Approach for the Retrieval of Images from Text Queries. ECML (2006)
David Grangier, Florent Monay, Samy Bengio
Learning to Retrieve Images from Text Queries with a Discriminative Model. Adaptive Multimedia Retrieval (2006)
David Grangier, Samy Bengio
A Neural Network to Retrieve Images from Text Queries. ICANN (2) (2006)
David Grangier, Samy Bengio
Inferring document similarity from hyperlinks. CIKM (2005)
David Grangier, Alessandro Vinciarelli
Effect of segmentation method on video retrieval performance. ICME (2005)

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Publication Activity (10 Years)

Top Topics

Top Venues

David Grangier