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ORCIDGrégoire Mialon
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2020 – today
- 2024
[c5]Grégoire Mialon, Clémentine Fourrier, Thomas Wolf, Yann LeCun, Thomas Scialom:
GAIA: a benchmark for General AI Assistants. ICLR 2024- [i12]Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, Anirudh Goyal, Anthony Hartshorn, Aobo Yang, Archi Mitra, Archie Sravankumar, Artem Korenev, Arthur Hinsvark, Arun Rao, Aston Zhang, Aurélien Rodriguez, Austen Gregerson, Ava Spataru, Baptiste Rozière, Bethany Biron, Binh Tang, Bobbie Chern, Charlotte Caucheteux, Chaya Nayak, Chloe Bi, Chris Marra, Chris McConnell, Christian Keller, Christophe Touret, Chunyang Wu, Corinne Wong, Cristian Canton Ferrer, Cyrus Nikolaidis, Damien Allonsius, Daniel Song, Danielle Pintz, Danny Livshits, David Esiobu, Dhruv Choudhary, Dhruv Mahajan, Diego Garcia-Olano, Diego Perino, Dieuwke Hupkes, Egor Lakomkin, Ehab AlBadawy, Elina Lobanova, Emily Dinan, Eric Michael Smith, Filip Radenovic, Frank Zhang, Gabriel Synnaeve, Gabrielle Lee, Georgia Lewis Anderson, Graeme Nail, Grégoire Mialon, Guan Pang, Guillem Cucurell, Hailey Nguyen, Hannah Korevaar, Hu Xu, Hugo Touvron, Iliyan Zarov, Imanol Arrieta Ibarra, Isabel M. Kloumann, Ishan Misra, Ivan Evtimov, Jade Copet, Jaewon Lee, Jan Geffert, Jana Vranes, Jason Park, Jay Mahadeokar, Jeet Shah, Jelmer van der Linde, Jennifer Billock, Jenny Hong, Jenya Lee, Jeremy Fu, Jianfeng Chi, Jianyu Huang, Jiawen Liu, Jie Wang, Jiecao Yu, Joanna Bitton, Joe Spisak, Jongsoo Park, Joseph Rocca, Joshua Johnstun, Joshua Saxe, Junteng Jia, Kalyan Vasuden Alwala, Kartikeya Upasani, Kate Plawiak, Ke Li, Kenneth Heafield, Kevin Stone, et al.:
The Llama 3 Herd of Models. CoRR abs/2407.21783 (2024) - 2023
- [j1]Grégoire Mialon, Roberto Dessì, Maria Lomeli, Christoforos Nalmpantis, Ramakanth Pasunuru, Roberta Raileanu, Baptiste Rozière, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, Thomas Scialom:
Augmented Language Models: a Survey. Trans. Mach. Learn. Res. 2023 (2023) - [c4]Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak T. Kiani:
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations. NeurIPS 2023 - [i11]Grégoire Mialon, Roberto Dessì, Maria Lomeli, Christoforos Nalmpantis, Ramakanth Pasunuru, Roberta Raileanu, Baptiste Rozière, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, Thomas Scialom:
Augmented Language Models: a Survey. CoRR abs/2302.07842 (2023) - [i10]Grégoire Mialon:
On Inductive Biases for Machine Learning in Data Constrained Settings. CoRR abs/2302.10692 (2023) - [i9]Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, Adrien Bardes, Grégoire Mialon, Yuandong Tian, Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann LeCun, Micah Goldblum:
A Cookbook of Self-Supervised Learning. CoRR abs/2304.12210 (2023) - [i8]Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak Toussi Kiani:
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations. CoRR abs/2307.05432 (2023) - [i7]Grégoire Mialon, Clémentine Fourrier, Craig Swift, Thomas Wolf, Yann LeCun, Thomas Scialom:
GAIA: a benchmark for General AI Assistants. CoRR abs/2311.12983 (2023) - [i6]Youssef Benchekroun, Megi Dervishi, Mark Ibrahim, Jean-Baptiste Gaya, Xavier Martinet, Grégoire Mialon, Thomas Scialom, Emmanuel Dupoux, Dieuwke Hupkes, Pascal Vincent:
WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language Models. CoRR abs/2311.15930 (2023) - 2022
- [b1]Grégoire Mialon:
On Inductive Biases for Machine Learning in Data Constrained Settings. (Biais inductifs pour l'apprentissage automatique à partir de données limitées). École Normale Supérieure, Paris, France, 2022 - [i5]Grégoire Mialon, Randall Balestriero, Yann LeCun:
Variance Covariance Regularization Enforces Pairwise Independence in Self-Supervised Representations. CoRR abs/2209.14905 (2022) - 2021
- [c3]Grégoire Mialon, Dexiong Chen, Alexandre d'Aspremont, Julien Mairal:
A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention. ICLR 2021 - [i4]Grégoire Mialon, Dexiong Chen, Margot Selosse, Julien Mairal:
GraphiT: Encoding Graph Structure in Transformers. CoRR abs/2106.05667 (2021) - 2020
- [c2]Grégoire Mialon, Julien Mairal, Alexandre d'Aspremont:
Screening Data Points in Empirical Risk Minimization via Ellipsoidal Regions and Safe Loss Functions. AISTATS 2020: 3610-3620 - [i3]Grégoire Mialon, Dexiong Chen, Alexandre d'Aspremont, Julien Mairal:
An Optimal Transport Kernel for Feature Aggregation and its Relationship to Attention. CoRR abs/2006.12065 (2020)
2010 – 2019
- 2019
- [c1]Alberto Bietti, Grégoire Mialon, Dexiong Chen, Julien Mairal:
A Kernel Perspective for Regularizing Deep Neural Networks. ICML 2019: 664-674 - [i2]Grégoire Mialon, Alexandre d'Aspremont, Julien Mairal:
Screening Data Points in Empirical Risk Minimization via Ellipsoidal Regions and Safe Loss Function. CoRR abs/1912.02566 (2019) - 2018
- [i1]Alberto Bietti, Grégoire Mialon, Julien Mairal:
On Regularization and Robustness of Deep Neural Networks. CoRR abs/1810.00363 (2018)
Coauthor Index
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