Inferring document similarity from hyperlinks. - David Grangier; Samy Bengio (CIKM, 2005)

Effect of segmentation method on video retrieval performance. - David Grangier; Alessandro Vinciarelli (ICME, 2005)

Learning to Retrieve Images from Text Queries with a Discriminative Model. - David Grangier; Florent Monay; Samy Bengio (Adaptive Multimedia Retrieval, 2006)

A Discriminative Approach for the Retrieval of Images from Text Queries. - David Grangier; Florent Monay; Samy Bengio (ECML, 2006)

A Neural Network to Retrieve Images from Text Queries. - David Grangier; Samy Bengio (ICANN (2), 2006)

Learning the inter-frame distance for discriminative template-based keyword detection. - David Grangier; Samy Bengio (INTERSPEECH, 2007)

A Discriminative Kernel-Based Approach to Rank Images from Text Queries. - David Grangier; Samy Bengio (IEEE Trans. Pattern Anal. Mach. Intell., 2008)

Supervised semantic indexing. - Bing Bai; Jason Weston; David Grangier; Ronan Collobert; Kunihiko Sadamasa; Yanjun Qi; Olivier Chapelle; Kilian Q. Weinberger (CIKM, 2009)

Supervised Semantic Indexing. - Bing Bai; Jason Weston; Ronan Collobert; David Grangier (ECIR, 2009)

Polynomial Semantic Indexing. - Bing Bai; Jason Weston; David Grangier; Ronan Collobert; Kunihiko Sadamasa; Yanjun Qi; Corinna Cortes; Mehryar Mohri (NIPS, 2009)

Discriminative keyword spotting. - Joseph Keshet; David Grangier; Samy Bengio (Speech Commun., 2009)

Label Embedding Trees for Large Multi-Class Tasks. - Samy Bengio; Jason Weston; David Grangier (NIPS, 2010)

Feature Set Embedding for Incomplete Data. - David Grangier; Iain Melvin (NIPS, 2010)

Learning to rank with (a lot of) word features. - Bing Bai; Jason Weston; David Grangier; Ronan Collobert; Kunihiko Sadamasa; Yanjun Qi; Olivier Chapelle; Kilian Q. Weinberger (Inf. Retr., 2010)

Half Transductive Ranking. - Bing Bai; Jason Weston; David Grangier; Ronan Collobert; Corinna Cortes; Mehryar Mohri (AISTATS, 2010)

Learning from Heterogeneous Sources via Gradient Boosting Consensus. - Xiaoxiao Shi; Jean-François Paiement; David Grangier; Philip S. Yu (SDM, 2012)

ICE: Enabling Non-Experts to Build Models Interactively for Large-Scale Lopsided Problems. - 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 (CoRR, 2014)

GBC: Gradient boosting consensus model for heterogeneous data. - Xiaoxiao Shi; Jean-François Paiement; David Grangier; Philip S. Yu (Stat. Anal. Data Min., 2014)

Strategies for Training Large Vocabulary Neural Language Models. - Wenlin Chen; David Grangier; Michael Auli (ACL (1), 2016)

Neural Text Generation from Structured Data with Application to the Biography Domain. - Rémi Lebret; David Grangier; Michael Auli (EMNLP, 2016)

Predicting distributions with Linearizing Belief Networks. - Yann N. Dauphin; David Grangier (ICLR (Poster), 2016)

Interactive Semantic Featuring for Text Classification. - Camille Jandot; Patrice Y. Simard; Max Chickering; David Grangier; Jina Suh (CoRR, 2016)

Vocabulary Selection Strategies for Neural Machine Translation. - Gurvan L'Hostis; David Grangier; Michael Auli (CoRR, 2016)

Generating Text from Structured Data with Application to the Biography Domain. - Rémi Lebret; David Grangier; Michael Auli (CoRR, 2016)

Iterative Refinement for Machine Translation. - Roman Novak; Michael Auli; David Grangier (CoRR, 2016)

A Convolutional Encoder Model for Neural Machine Translation. - Jonas Gehring; Michael Auli; David Grangier; Yann N. Dauphin (ACL (1), 2017)

Language Modeling with Gated Convolutional Networks. - Yann N. Dauphin; Angela Fan; Michael Auli; David Grangier (ICML, 2017)

Convolutional Sequence to Sequence Learning. - Jonas Gehring; Michael Auli; David Grangier; Denis Yarats; Yann N. Dauphin (ICML, 2017)

Efficient softmax approximation for GPUs. - Edouard Grave; Armand Joulin; Moustapha Cissé; David Grangier; Hervé Jégou (ICML, 2017)

QuickEdit: Editing Text & Translations via Simple Delete Actions. - David Grangier; Michael Auli (CoRR, 2017)

Controllable Abstractive Summarization. - Angela Fan; David Grangier; Michael Auli (NMT@ACL, 2018)

QuaterNet: A Quaternion-based Recurrent Model for Human Motion. - Dario Pavllo; David Grangier; Michael Auli (BMVC, 2018)

Understanding Back-Translation at Scale. - Sergey Edunov; Myle Ott; Michael Auli; David Grangier (EMNLP, 2018)

Analyzing Uncertainty in Neural Machine Translation. - Myle Ott; Michael Auli; David Grangier; Marc'Aurelio Ranzato (ICML, 2018)

Classical Structured Prediction Losses for Sequence to Sequence Learning. - Sergey Edunov; Myle Ott; Michael Auli; David Grangier; Marc'Aurelio Ranzato (NAACL-HLT, 2018)

QuickEdit: Editing Text & Translations by Crossing Words Out. - David Grangier; Michael Auli (NAACL-HLT, 2018)

Scaling Neural Machine Translation. - Myle Ott; Sergey Edunov; David Grangier; Michael Auli (WMT, 2018)

ELI5: Long Form Question Answering. - Angela Fan; Yacine Jernite; Ethan Perez; David Grangier; Jason Weston; Michael Auli (ACL (1), 2019)

Unsupervised Paraphrasing without Translation. - Aurko Roy; David Grangier (ACL (1), 2019)

3D Human Pose Estimation in Video With Temporal Convolutions and Semi-Supervised Training. - Dario Pavllo; Christoph Feichtenhofer; David Grangier; Michael Auli (CVPR, 2019)

fairseq: A Fast, Extensible Toolkit for Sequence Modeling. - Myle Ott; Sergey Edunov; Alexei Baevski; Angela Fan; Sam Gross; Nathan Ng 001; David Grangier; Michael Auli (NAACL-HLT (Demonstrations), 2019)

Tagged Back-Translation. - Isaac Caswell; Ciprian Chelba; David Grangier (WMT (1), 2019)

Toward Better Storylines with Sentence-Level Language Models. - Daphne Ippolito; David Grangier; Douglas Eck; Chris Callison-Burch (ACL, 2020)

Translationese as a Language in "Multilingual" NMT. - Parker Riley; Isaac Caswell; Markus Freitag; David Grangier (ACL, 2020)

BLEU might be Guilty but References are not Innocent. - Markus Freitag; David Grangier; Isaac Caswell (EMNLP (1), 2020)

Human-Paraphrased References Improve Neural Machine Translation. - Markus Freitag; George F. Foster; David Grangier; Colin Cherry (WMT@EMNLP, 2020)

Modeling Human Motion with Quaternion-Based Neural Networks. - Dario Pavllo; Christoph Feichtenhofer; Michael Auli; David Grangier (Int. J. Comput. Vis., 2020)

Dive: End-to-End Speech Diarization Via Iterative Speaker Embedding. - Neil Zeghidour; Olivier Teboul; David Grangier (ASRU, 2021)

Learning From Heterogeneous Eeg Signals with Differentiable Channel Reordering. - Aaqib Saeed; David Grangier; Olivier Pietquin; Neil Zeghidour (ICASSP, 2021)

Contrastive Learning of General-Purpose Audio Representations. - Aaqib Saeed; David Grangier; Neil Zeghidour (ICASSP, 2021)

Auxiliary Task Update Decomposition: the Good, the Bad and the neutral. - Lucio M. Dery; Yann N. Dauphin; David Grangier (ICLR, 2021)

What Can Unsupervised Machine Translation Contribute to High-Resource Language Pairs? - Kelly Marchisio; Markus Freitag; David Grangier (CoRR, 2021)

On the Complementarity of Data Selection and Fine Tuning for Domain Adaptation. - Dan Iter; David Grangier (CoRR, 2021)

Minimum Bayes Risk Decoding with Neural Metrics of Translation Quality. - Markus Freitag; David Grangier; Qijun Tan; Bowen Liang (CoRR, 2021)

Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation. - Markus Freitag; George F. Foster; David Grangier; Viresh Ratnakar; Qijun Tan; Wolfgang Macherey (Trans. Assoc. Comput. Linguistics, 2021)

Efficient Content-Based Sparse Attention with Routing Transformers. - Aurko Roy; Mohammad Saffar; Ashish Vaswani; David Grangier (Trans. Assoc. Comput. Linguistics, 2021)

Wavesplit: End-to-End Speech Separation by Speaker Clustering. - Neil Zeghidour; David Grangier (IEEE ACM Trans. Audio Speech Lang. Process., 2021)

A Natural Diet: Towards Improving Naturalness of Machine Translation Output. - Markus Freitag; David Vilar; David Grangier; Colin Cherry; George F. Foster (ACL (Findings), 2022)

The Trade-offs of Domain Adaptation for Neural Language Models. - David Grangier; Dan Iter (ACL (1), 2022)

Learning Strides in Convolutional Neural Networks. - Rachid Riad; Olivier Teboul; David Grangier; Neil Zeghidour (ICLR, 2022)

On Systematic Style Differences between Unsupervised and Supervised MT and an Application for High-Resource Machine Translation. - Kelly Marchisio; Markus Freitag; David Grangier (NAACL-HLT, 2022)

AudioLM: a Language Modeling Approach to Audio Generation. - Zalán Borsos; Raphaël Marinier; Damien Vincent; Eugene Kharitonov; Olivier Pietquin; Matthew Sharifi; Olivier Teboul; David Grangier; Marco Tagliasacchi; Neil Zeghidour (CoRR, 2022)

High-Resource Methodological Bias in Low-Resource Investigations. - Maartje ter Hoeve; David Grangier; Natalie Schluter (CoRR, 2022)

High Quality Rather than High Model Probability: Minimum Bayes Risk Decoding with Neural Metrics. - Markus Freitag; David Grangier; Qijun Tan; Bowen Liang (Trans. Assoc. Comput. Linguistics, 2022)

Transfer Learning for Structured Pruning under Limited Task Data. - Lucio M. Dery; David Grangier; Awni Hannun (CoRR, 2023)

AudioLM: A Language Modeling Approach to Audio Generation. - Zalán Borsos; Raphaël Marinier; Damien Vincent; Eugene Kharitonov; Olivier Pietquin; Matthew Sharifi; Dominik Roblek; Olivier Teboul; David Grangier; Marco Tagliasacchi; Neil Zeghidour (IEEE ACM Trans. Audio Speech Lang. Process., 2023)

Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling. - Pratyush Maini; Skyler Seto; Richard He Bai; David Grangier; Yizhe Zhang 002; Navdeep Jaitly (ACL (1), 2024)

Aggregate-and-Adapt Natural Language Prompts for Downstream Generalization of CLIP. - Chen Huang 001; Skyler Seto; Samira Abnar; David Grangier; Navdeep Jaitly; Joshua M. Susskind (NeurIPS, 2024)

Specialized Language Models with Cheap Inference from Limited Domain Data. - David Grangier; Angelos Katharopoulos; Pierre Ablin; Awni Hannun (CoRR, 2024)

Dynamic Gradient Alignment for Online Data Mixing. - Simin Fan; David Grangier; Pierre Ablin (CoRR, 2024)

Adaptive Training Distributions with Scalable Online Bilevel Optimization. - David Grangier; Pierre Ablin; Awni Hannun (Trans. Mach. Learn. Res., 2024)

Training Bilingual LMs with Data Constraints in the Targeted Language. - Skyler Seto; Maartje ter Hoeve; Richard He Bai; Natalie Schluter; David Grangier (ACL (Findings), 2025)

No Need to Talk: Asynchronous Mixture of Language Models. - Anastasiia Filippova; Angelos Katharopoulos; David Grangier; Ronan Collobert (ICLR, 2025)

Task-Adaptive Pretrained Language Models via Clustered-Importance Sampling. - David Grangier; Simin Fan; Skyler Seto; Pierre Ablin (ICLR, 2025)

The AdEMAMix Optimizer: Better, Faster, Older. - Matteo Pagliardini; Pierre Ablin; David Grangier (ICLR, 2025)

Soup-of-Experts: Pretraining Specialist Models via Parameters Averaging. - Pierre Ablin; Angelos Katharopoulos; Skyler Seto; David Grangier (CoRR, 2025)

Scaling Laws for Forgetting during Finetuning with Pretraining Data Injection. - Louis Béthune; David Grangier; Dan Busbridge; Eleonora Gualdoni; Marco Cuturi; Pierre Ablin (CoRR, 2025)

Assessing the Role of Data Quality in Training Bilingual Language Models. - Skyler Seto; Maartje ter Hoeve; Maureen de Seyssel; David Grangier (CoRR, 2025)

Scaling Laws for Optimal Data Mixtures. - Mustafa Shukor; Louis Béthune; Dan Busbridge; David Grangier; Enrico Fini; Alaaeldin El-Nouby; Pierre Ablin (CoRR, 2025)