Grangier, David

25 publications

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

ICML 2025 Scaling Laws for Forgetting During Finetuning with Pretraining Data Injection Louis Béthune, David Grangier, Dan Busbridge, Eleonora Gualdoni, Marco Cuturi, Pierre Ablin

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

ICML 2025 Soup-of-Experts: Pretraining Specialist Models via Parameters Averaging Pierre Ablin, Angelos Katharopoulos, Skyler Seto, David Grangier

ICLRW 2025 Soup-of-Experts: Pretraining Specialist Models via Parameters Averaging Pierre Ablin, Angelos Katharopoulos, Skyler Seto, David Grangier

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

NeurIPSW 2024 AdEMAMix: Better and Faster Training with Older Gradients Matteo Pagliardini, Pierre Ablin, David Grangier

TMLR 2024 Adaptive Training Distributions with Scalable Online Bilevel Optimization David Grangier, Pierre Ablin, Awni Hannun

NeurIPS 2024 Aggregate-and-Adapt Natural Language Prompts for Downstream Generalization of CLIP Chen Huang, Skyler Seto, Samira Abnar, David Grangier, Navdeep Jaitly, Josh Susskind

ICMLW 2024 Projected Language Models: A Large Model Pre-Segmented into Smaller Ones David Grangier, Angelos Katharopoulos, Pierre Ablin, Awni Hannun

ICLRW 2024 Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling Pratyush Maini, Skyler Seto, He Bai, David Grangier, Yizhe Zhang, Navdeep Jaitly

NeurIPSW 2023 Bilevel Optimization to Learn Training Distributions for Language Modeling Under Domain Shift David Grangier, Pierre Ablin, Awni Hannun

ICLR 2022 Learning Strides in Convolutional Neural Networks Rachid Riad, Olivier Teboul, David Grangier, Neil Zeghidour

ICLR 2021 Auxiliary Task Update Decomposition: The Good, the Bad and the Neutral Lucio M. Dery, Yann Dauphin, David Grangier

ICML 2018 Analyzing Uncertainty in Neural Machine Translation Myle Ott, Michael Auli, David Grangier, Marc’Aurelio Ranzato

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 Grave, Armand Joulin, Moustapha Cissé, David Grangier, Hervé Jégou

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

ICLR 2016 Predicting Distributions with Linearizing Belief Networks Yann N. Dauphin, David Grangier

NeurIPS 2010 Feature Set Embedding for Incomplete Data David Grangier, Iain Melvin

AISTATS 2010 Half Transductive Ranking Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Corinna Cortes, Mehryar Mohri

NeurIPS 2010 Label Embedding Trees for Large Multi-Class Tasks Samy Bengio, Jason Weston, David Grangier

NeurIPS 2009 Polynomial Semantic Indexing Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Corinna Cortes, Mehryar Mohri

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