Badr Youbi Idrissi

13 papers A* 2Journal 9Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Beyond Multi-Token Prediction: Pretraining LLMs with Future Summaries. CoRR Divyat Mahajan, Sachin Goyal, Badr Youbi Idrissi, Mohammad Pezeshki, Ioannis Mitliagkas, David Lopez-Paz, Kartik Ahuja
2025	J	`jnl`	CWM: An Open-Weights LLM for Research on Code Generation with World Models. CoRR 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
2025	J	`jnl`	From Bytes to Ideas: Language Modeling with Autoregressive U-Nets. CoRR Mathurin Videau, Badr Youbi Idrissi, Alessandro Ferreira Leite, Marc Schoenauer, Olivier Teytaud, David Lopez-Paz
2025	J	`jnl`	Temperature Matters: Enhancing Watermark Robustness Against Paraphrasing Attacks. CoRR Badr Youbi Idrissi, Monica Millunzi, Amelia Sorrenti, Lorenzo Baraldi, Daryna Dementieva
2024	A*	`conf`	Better & Faster Large Language Models via Multi-token Prediction. ICML Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Rozière, David Lopez-Paz, Gabriel Synnaeve
2024	J	`jnl`	Better & Faster Large Language Models via Multi-token Prediction. CoRR Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Rozière, David Lopez-Paz, Gabriel Synnaeve
2023	A*	`conf`	ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. ICLR Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim
2022	J	`jnl`	ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. CoRR Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim
2022	—	`conf`	Simple data balancing achieves competitive worst-group-accuracy. CLeaR Badr Youbi Idrissi, Martín Arjovsky, Mohammad Pezeshki, David Lopez-Paz
2021	J	`jnl`	Masked Adversarial Generation for Neural Machine Translation. CoRR Badr Youbi Idrissi, Stéphane Clinchant
2021	J	`jnl`	Simple data balancing achieves competitive worst-group-accuracy. CoRR Badr Youbi Idrissi, Martín Arjovsky, Mohammad Pezeshki, David Lopez-Paz
2021	—	`conf`	VirAAL: Virtual Adversarial Active Learning for NLU. SLT Grégory Senay, Badr Youbi Idrissi, Marine Haziza
2020	J	`jnl`	VirAAL: Virtual Adversarial Active Learning. CoRR Grégory Senay, Badr Youbi Idrissi, Marine Haziza

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.