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ORCIDBadr Youbi Idrissi
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2020 – today
- 2025
[i9]Mathurin Videau, Badr Youbi Idrissi, Alessandro Ferreira Leite, Marc Schoenauer, Olivier Teytaud, David Lopez-Paz:
From Bytes to Ideas: Language Modeling with Autoregressive U-Nets. CoRR abs/2506.14761 (2025)- [i8]Badr Youbi Idrissi, Monica Millunzi, Amelia Sorrenti, Lorenzo Baraldi, Daryna Dementieva:
Temperature Matters: Enhancing Watermark Robustness Against Paraphrasing Attacks. CoRR abs/2506.22623 (2025) - [i7]FAIR CodeGen team, Jade Copet, Quentin Carbonneaux, Gal Cohen, Jonas Gehring, Jacob Kahn, Jannik Kossen, Felix Kreuk, Emily McMilin, Michel Meyer, Yuxiang Wei, David Zhang, Kunhao Zheng, Jordi Armengol-Estapé, Pedram Bashiri, Maximilian Beck, Pierre Chambon, Abhishek Charnalia, Chris Cummins, Juliette Decugis, Zacharias V. Fisches, François Fleuret, Fabian Gloeckle, Alex Gu, Michael Hassid, Daniel Haziza, Badr Youbi Idrissi, Christian Keller, Rahul Kindi, Hugh Leather, Gallil Maimon, Aram H. Markosyan, Francisco Massa, Pierre-Emmanuel Mazaré, Vegard Mella, Naila Murray, Keyur Muzumdar, Peter W. O'Hearn, Matteo Pagliardini, Dmitrii Pedchenko, Tal Remez, Volker Seeker, Marco Selvi
, Oren Sultan, Sida Wang, Luca Wehrstedt, Ori Yoran, Lingming Zhang, Taco Cohen, Yossi Adi, Gabriel Synnaeve:
CWM: An Open-Weights LLM for Research on Code Generation with World Models. CoRR abs/2510.02387 (2025) - [i6]Divyat Mahajan, Sachin Goyal, Badr Youbi Idrissi, Mohammad Pezeshki, Ioannis Mitliagkas, David Lopez-Paz, Kartik Ahuja:
Beyond Multi-Token Prediction: Pretraining LLMs with Future Summaries. CoRR abs/2510.14751 (2025) - 2024
- [c4]Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Rozière, David Lopez-Paz, Gabriel Synnaeve:
Better & Faster Large Language Models via Multi-token Prediction. ICML 2024: 15706-15734 - [i5]Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Rozière, David Lopez-Paz, Gabriel Synnaeve:
Better & Faster Large Language Models via Multi-token Prediction. CoRR abs/2404.19737 (2024) - 2023
- [c3]Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim:
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. ICLR 2023 - 2022
- [c2]Badr Youbi Idrissi, Martín Arjovsky, Mohammad Pezeshki, David Lopez-Paz:
Simple data balancing achieves competitive worst-group-accuracy. CLeaR 2022: 336-351 - [i4]Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim:
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. CoRR abs/2211.01866 (2022) - 2021
- [c1]Grégory Senay, Badr Youbi Idrissi, Marine Haziza:
VirAAL: Virtual Adversarial Active Learning for NLU. SLT 2021: 973-980 - [i3]Badr Youbi Idrissi, Stéphane Clinchant:
Masked Adversarial Generation for Neural Machine Translation. CoRR abs/2109.00417 (2021) - [i2]Badr Youbi Idrissi, Martín Arjovsky, Mohammad Pezeshki, David Lopez-Paz:
Simple data balancing achieves competitive worst-group-accuracy. CoRR abs/2110.14503 (2021) - 2020
- [i1]Grégory Senay, Badr Youbi Idrissi, Marine Haziza:
VirAAL: Virtual Adversarial Active Learning. CoRR abs/2005.07287 (2020)
Coauthor Index
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