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2020 – today
- 2024
[c45]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: 14044-14072- [i51]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 abs/2401.16380 (2024) - [i50]David Grangier, Angelos Katharopoulos, Pierre Ablin, Awni Hannun:
Specialized Language Models with Cheap Inference from Limited Domain Data. CoRR abs/2402.01093 (2024) - [i49]Matteo Pagliardini, Pierre Ablin, David Grangier:
The AdEMAMix Optimizer: Better, Faster, Older. CoRR abs/2409.03137 (2024) - [i48]Simin Fan, David Grangier, Pierre Ablin:
Dynamic Gradient Alignment for Online Data Mixing. CoRR abs/2410.02498 (2024) - [i47]Anastasiia Filippova, Angelos Katharopoulos, David Grangier, Ronan Collobert:
No Need to Talk: Asynchronous Mixture of Language Models. CoRR abs/2410.03529 (2024) - [i46]David Grangier, Simin Fan, Skyler Seto, Pierre Ablin:
Task-Adaptive Pretrained Language Models via Clustered-Importance Sampling. CoRR abs/2410.03735 (2024) - [i45]Chen Huang, Skyler Seto, Samira Abnar, David Grangier, Navdeep Jaitly, Josh M. Susskind:
Aggregate-and-Adapt Natural Language Prompts for Downstream Generalization of CLIP. CoRR abs/2410.23698 (2024) - [i44]Skyler Seto, Maartje ter Hoeve, He Bai, Natalie Schluter, David Grangier:
Training Bilingual LMs with Data Constraints in the Targeted Language. CoRR abs/2411.12986 (2024) - 2023
- [j10]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: 2523-2533 (2023) - [i43]Lucio M. Dery, David Grangier, Awni Hannun:
Transfer Learning for Structured Pruning under Limited Task Data. CoRR abs/2311.06382 (2023) - [i42]David Grangier, Pierre Ablin, Awni Hannun:
Adaptive Training Distributions with Scalable Online Bilevel Optimization. CoRR abs/2311.11973 (2023) - 2022
- [j9]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: 811-825 (2022) - [c44]Markus Freitag, David Vilar, David Grangier, Colin Cherry, George F. Foster:
A Natural Diet: Towards Improving Naturalness of Machine Translation Output. ACL (Findings) 2022: 3340-3353 - [c43]David Grangier, Dan Iter:
The Trade-offs of Domain Adaptation for Neural Language Models. ACL (1) 2022: 3802-3813 - [c42]Rachid Riad, Olivier Teboul, David Grangier, Neil Zeghidour:
Learning Strides in Convolutional Neural Networks. ICLR 2022 - [c41]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: 2214-2225 - [i41]Rachid Riad, Olivier Teboul, David Grangier, Neil Zeghidour:
Learning strides in convolutional neural networks. CoRR abs/2202.01653 (2022) - [i40]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 abs/2209.03143 (2022) - [i39]Maartje ter Hoeve, David Grangier, Natalie Schluter:
High-Resource Methodological Bias in Low-Resource Investigations. CoRR abs/2211.07534 (2022) - 2021
- [j8]Aurko Roy, Mohammad Saffar, Ashish Vaswani, David Grangier:
Efficient Content-Based Sparse Attention with Routing Transformers. Trans. Assoc. Comput. Linguistics 9: 53-68 (2021) - [j7]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: 1460-1474 (2021) - [j6]Neil Zeghidour, David Grangier:
Wavesplit: End-to-End Speech Separation by Speaker Clustering. IEEE ACM Trans. Audio Speech Lang. Process. 29: 2840-2849 (2021) - [c40]Neil Zeghidour, Olivier Teboul, David Grangier:
Dive: End-to-End Speech Diarization Via Iterative Speaker Embedding. ASRU 2021: 702-709 - [c39]Aaqib Saeed, David Grangier, Olivier Pietquin, Neil Zeghidour:
Learning From Heterogeneous Eeg Signals with Differentiable Channel Reordering. ICASSP 2021: 1255-1259 - [c38]Aaqib Saeed, David Grangier, Neil Zeghidour:
Contrastive Learning of General-Purpose Audio Representations. ICASSP 2021: 3875-3879 - [c37]Lucio M. Dery, Yann N. Dauphin, David Grangier:
Auxiliary Task Update Decomposition: the Good, the Bad and the neutral. ICLR 2021 - [i38]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 abs/2104.14478 (2021) - [i37]Neil Zeghidour, Olivier Teboul, David Grangier:
DIVE: End-to-end Speech Diarization via Iterative Speaker Embedding. CoRR abs/2105.13802 (2021) - [i36]Kelly Marchisio, Markus Freitag, David Grangier:
What Can Unsupervised Machine Translation Contribute to High-Resource Language Pairs? CoRR abs/2106.15818 (2021) - [i35]Lucio M. Dery, Yann N. Dauphin, David Grangier:
Auxiliary Task Update Decomposition: The Good, The Bad and The Neutral. CoRR abs/2108.11346 (2021) - [i34]Dan Iter, David Grangier:
On the Complementarity of Data Selection and Fine Tuning for Domain Adaptation. CoRR abs/2109.07591 (2021) - [i33]Dan Iter, David Grangier:
The Trade-offs of Domain Adaptation for Neural Language Models. CoRR abs/2109.10274 (2021) - [i32]Markus Freitag, David Grangier, Qijun Tan, Bowen Liang:
Minimum Bayes Risk Decoding with Neural Metrics of Translation Quality. CoRR abs/2111.09388 (2021) - 2020
- [j5]Dario Pavllo, Christoph Feichtenhofer, Michael Auli, David Grangier:
Modeling Human Motion with Quaternion-Based Neural Networks. Int. J. Comput. Vis. 128(4): 855-872 (2020) - [c36]Daphne Ippolito, David Grangier, Douglas Eck, Chris Callison-Burch:
Toward Better Storylines with Sentence-Level Language Models. ACL 2020: 7472-7478 - [c35]Parker Riley, Isaac Caswell, Markus Freitag, David Grangier:
Translationese as a Language in "Multilingual" NMT. ACL 2020: 7737-7746 - [c34]Markus Freitag, David Grangier, Isaac Caswell:
BLEU might be Guilty but References are not Innocent. EMNLP (1) 2020: 61-71 - [c33]Markus Freitag, George F. Foster, David Grangier, Colin Cherry:
Human-Paraphrased References Improve Neural Machine Translation. WMT@EMNLP 2020: 1183-1192 - [i31]Neil Zeghidour, David Grangier:
Wavesplit: End-to-End Speech Separation by Speaker Clustering. CoRR abs/2002.08933 (2020) - [i30]Aurko Roy, Mohammad Saffar, Ashish Vaswani, David Grangier:
Efficient Content-Based Sparse Attention with Routing Transformers. CoRR abs/2003.05997 (2020) - [i29]Markus Freitag, David Grangier, Isaac Caswell:
BLEU might be Guilty but References are not Innocent. CoRR abs/2004.06063 (2020) - [i28]Daphne Ippolito, David Grangier, Douglas Eck, Chris Callison-Burch:
Toward Better Storylines with Sentence-Level Language Models. CoRR abs/2005.05255 (2020) - [i27]Markus Freitag, George F. Foster, David Grangier, Colin Cherry:
Human-Paraphrased References Improve Neural Machine Translation. CoRR abs/2010.10245 (2020) - [i26]Aaqib Saeed, David Grangier, Neil Zeghidour:
Contrastive Learning of General-Purpose Audio Representations. CoRR abs/2010.10915 (2020) - [i25]Aaqib Saeed, David Grangier, Olivier Pietquin, Neil Zeghidour:
Learning from Heterogeneous EEG Signals with Differentiable Channel Reordering. CoRR abs/2010.13694 (2020)
2010 – 2019
- 2019
- [c32]Angela Fan, Yacine Jernite, Ethan Perez, David Grangier, Jason Weston, Michael Auli:
ELI5: Long Form Question Answering. ACL (1) 2019: 3558-3567 - [c31]Aurko Roy, David Grangier:
Unsupervised Paraphrasing without Translation. ACL (1) 2019: 6033-6039 - [c30]Dario Pavllo, Christoph Feichtenhofer, David Grangier, Michael Auli:
3D Human Pose Estimation in Video With Temporal Convolutions and Semi-Supervised Training. CVPR 2019: 7753-7762 - [c29]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: 48-53 - [c28]Isaac Caswell, Ciprian Chelba, David Grangier:
Tagged Back-Translation. WMT (1) 2019: 53-63 - [i24]Dario Pavllo, Christoph Feichtenhofer, Michael Auli, David Grangier:
Modeling Human Motion with Quaternion-based Neural Networks. CoRR abs/1901.07677 (2019) - [i23]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 abs/1904.01038 (2019) - [i22]Aurko Roy, David Grangier:
Unsupervised Paraphrasing without Translation. CoRR abs/1905.12752 (2019) - [i21]Isaac Caswell, Ciprian Chelba, David Grangier:
Tagged Back-Translation. CoRR abs/1906.06442 (2019) - [i20]Angela Fan, Yacine Jernite, Ethan Perez, David Grangier, Jason Weston, Michael Auli:
ELI5: Long Form Question Answering. CoRR abs/1907.09190 (2019) - [i19]Parker Riley, Isaac Caswell, Markus Freitag, David Grangier:
Translationese as a Language in "Multilingual" NMT. CoRR abs/1911.03823 (2019) - 2018
- [c27]Angela Fan, David Grangier, Michael Auli:
Controllable Abstractive Summarization. NMT@ACL 2018: 45-54 - [c26]Dario Pavllo, David Grangier, Michael Auli:
QuaterNet: A Quaternion-based Recurrent Model for Human Motion. BMVC 2018: 299 - [c25]Sergey Edunov, Myle Ott, Michael Auli, David Grangier:
Understanding Back-Translation at Scale. EMNLP 2018: 489-500 - [c24]Myle Ott, Michael Auli, David Grangier, Marc'Aurelio Ranzato:
Analyzing Uncertainty in Neural Machine Translation. ICML 2018: 3953-3962 - [c23]David Grangier, Michael Auli:
QuickEdit: Editing Text & Translations by Crossing Words Out. NAACL-HLT 2018: 272-282 - [c22]Sergey Edunov, Myle Ott, Michael Auli, David Grangier, Marc'Aurelio Ranzato:
Classical Structured Prediction Losses for Sequence to Sequence Learning. NAACL-HLT 2018: 355-364 - [c21]Myle Ott, Sergey Edunov, David Grangier, Michael Auli:
Scaling Neural Machine Translation. WMT 2018: 1-9 - [i18]Myle Ott, Michael Auli, David Grangier, Marc'Aurelio Ranzato:
Analyzing Uncertainty in Neural Machine Translation. CoRR abs/1803.00047 (2018) - [i17]Dario Pavllo, David Grangier, Michael Auli:
QuaterNet: A Quaternion-based Recurrent Model for Human Motion. CoRR abs/1805.06485 (2018) - [i16]Myle Ott, Sergey Edunov, David Grangier, Michael Auli:
Scaling Neural Machine Translation. CoRR abs/1806.00187 (2018) - [i15]Sergey Edunov, Myle Ott, Michael Auli, David Grangier:
Understanding Back-Translation at Scale. CoRR abs/1808.09381 (2018) - [i14]Dario Pavllo, Christoph Feichtenhofer, David Grangier, Michael Auli:
3D human pose estimation in video with temporal convolutions and semi-supervised training. CoRR abs/1811.11742 (2018) - 2017
- [c20]Jonas Gehring, Michael Auli, David Grangier, Yann N. Dauphin:
A Convolutional Encoder Model for Neural Machine Translation. ACL (1) 2017: 123-135 - [c19]Yann N. Dauphin, Angela Fan, Michael Auli, David Grangier:
Language Modeling with Gated Convolutional Networks. ICML 2017: 933-941 - [c18]Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin:
Convolutional Sequence to Sequence Learning. ICML 2017: 1243-1252 - [c17]Edouard Grave, Armand Joulin, Moustapha Cissé, David Grangier, Hervé Jégou:
Efficient softmax approximation for GPUs. ICML 2017: 1302-1310 - [i13]Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin:
Convolutional Sequence to Sequence Learning. CoRR abs/1705.03122 (2017) - [i12]David Grangier, Michael Auli:
QuickEdit: Editing Text & Translations via Simple Delete Actions. CoRR abs/1711.04805 (2017) - [i11]Sergey Edunov, Myle Ott, Michael Auli, David Grangier, Marc'Aurelio Ranzato:
Classical Structured Prediction Losses for Sequence to Sequence Learning. CoRR abs/1711.04956 (2017) - [i10]Angela Fan, David Grangier, Michael Auli:
Controllable Abstractive Summarization. CoRR abs/1711.05217 (2017) - 2016
- [c16]Wenlin Chen, David Grangier, Michael Auli:
Strategies for Training Large Vocabulary Neural Language Models. ACL (1) 2016 - [c15]Rémi Lebret, David Grangier, Michael Auli:
Neural Text Generation from Structured Data with Application to the Biography Domain. EMNLP 2016: 1203-1213 - [c14]Yann N. Dauphin, David Grangier:
Predicting distributions with Linearizing Belief Networks. ICLR (Poster) 2016 - [i9]Rémi Lebret, David Grangier, Michael Auli:
Generating Text from Structured Data with Application to the Biography Domain. CoRR abs/1603.07771 (2016) - [i8]Camille Jandot, Patrice Y. Simard, Max Chickering, David Grangier, Jina Suh:
Interactive Semantic Featuring for Text Classification. CoRR abs/1606.07545 (2016) - [i7]Edouard Grave, Armand Joulin, Moustapha Cissé, David Grangier, Hervé Jégou:
Efficient softmax approximation for GPUs. CoRR abs/1609.04309 (2016) - [i6]Gurvan L'Hostis, David Grangier, Michael Auli:
Vocabulary Selection Strategies for Neural Machine Translation. CoRR abs/1610.00072 (2016) - [i5]Roman Novak, Michael Auli, David Grangier:
Iterative Refinement for Machine Translation. CoRR abs/1610.06602 (2016) - [i4]Jonas Gehring, Michael Auli, David Grangier, Yann N. Dauphin:
A Convolutional Encoder Model for Neural Machine Translation. CoRR abs/1611.02344 (2016) - [i3]Yann N. Dauphin, Angela Fan, Michael Auli, David Grangier:
Language Modeling with Gated Convolutional Networks. CoRR abs/1612.08083 (2016) - 2015
- [i2]Wenlin Chen, David Grangier, Michael Auli:
Strategies for Training Large Vocabulary Neural Language Models. CoRR abs/1512.04906 (2015) - 2014
- [j4]Xiaoxiao Shi, Jean-François Paiement, David Grangier, Philip S. Yu:
GBC: Gradient boosting consensus model for heterogeneous data. Stat. Anal. Data Min. 7(3): 161-174 (2014) - [i1]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 abs/1409.4814 (2014) - 2012
- [c13]Xiaoxiao Shi, Jean-François Paiement, David Grangier, Philip S. Yu:
Learning from Heterogeneous Sources via Gradient Boosting Consensus. SDM 2012: 224-235 - 2010
- [j3]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): 291-314 (2010) - [c12]Samy Bengio, Jason Weston, David Grangier:
Label Embedding Trees for Large Multi-Class Tasks. NIPS 2010: 163-171 - [c11]David Grangier, Iain Melvin:
Feature Set Embedding for Incomplete Data. NIPS 2010: 793-801 - [c10]Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Corinna Cortes, Mehryar Mohri:
Half Transductive Ranking. AISTATS 2010: 49-56
2000 – 2009
- 2009
- [j2]Joseph Keshet, David Grangier, Samy Bengio:
Discriminative keyword spotting. Speech Commun. 51(4): 317-329 (2009) - [c9]Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Olivier Chapelle, Kilian Q. Weinberger:
Supervised semantic indexing. CIKM 2009: 187-196 - [c8]Bing Bai, Jason Weston, Ronan Collobert, David Grangier:
Supervised Semantic Indexing. ECIR 2009: 761-765 - [c7]Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Corinna Cortes, Mehryar Mohri:
Polynomial Semantic Indexing. NIPS 2009: 64-72 - 2008
- [j1]David Grangier, Samy Bengio:
A Discriminative Kernel-Based Approach to Rank Images from Text Queries. IEEE Trans. Pattern Anal. Mach. Intell. 30(8): 1371-1384 (2008) - 2007
- [c6]David Grangier, Samy Bengio:
Learning the inter-frame distance for discriminative template-based keyword detection. INTERSPEECH 2007: 902-905 - 2006
- [c5]David Grangier, Florent Monay, Samy Bengio:
Learning to Retrieve Images from Text Queries with a Discriminative Model. Adaptive Multimedia Retrieval 2006: 42-56 - [c4]David Grangier, Florent Monay, Samy Bengio:
A Discriminative Approach for the Retrieval of Images from Text Queries. ECML 2006: 162-173 - [c3]David Grangier, Samy Bengio:
A Neural Network to Retrieve Images from Text Queries. ICANN (2) 2006: 24-34 - 2005
- [c2]David Grangier, Samy Bengio:
Inferring document similarity from hyperlinks. CIKM 2005: 359-360 - [c1]David Grangier, Alessandro Vinciarelli:
Effect of segmentation method on video retrieval performance. ICME 2005: 5-8
Coauthor Index
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