Gautier Izacard

30 papers A* 4A 2Misc 1Journal 20Unranked 2

Year	Rank	Type	Title / Venue / Authors
2024	—	`—`	Augmenting language models with information retrieval. (Augmenter les modèles de langue avec des systèmes de recherche d'informations). Gautier Izacard
2023	J	`jnl`	Atlas: Few-shot Learning with Retrieval Augmented Language Models. J. Mach. Learn. Res. Gautier Izacard, Patrick Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, Edouard Grave
2023	J	`jnl`	Improving Wikipedia verifiability with AI. Nat. Mac. Intell. Fabio Petroni, Samuel Broscheit, Aleksandra Piktus, Patrick Lewis, Gautier Izacard, Lucas Hosseini, Jane Dwivedi-Yu, Maria Lomeli, Timo Schick, Michele Bevilacqua, Pierre-Emmanuel Mazaré, Armand Joulin, Edouard Grave, Sebastian Riedel
2023	J	`jnl`	LLaMA: Open and Efficient Foundation Language Models. CoRR Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurélien Rodriguez, Armand Joulin, Edouard Grave, Guillaume Lample
2023	A*	`conf`	PEER: A Collaborative Language Model. ICLR Timo Schick, Jane A. Yu, Zhengbao Jiang, Fabio Petroni, Patrick Lewis, Gautier Izacard, Qingfei You, Christoforos Nalmpantis, Edouard Grave, Sebastian Riedel
2023	J	`jnl`	ResMLP: Feedforward Networks for Image Classification With Data-Efficient Training. IEEE Trans. Pattern Anal. Mach. Intell. Hugo Touvron, Piotr Bojanowski, Mathilde Caron, Matthieu Cord, Alaaeldin El-Nouby, Edouard Grave, Gautier Izacard, Armand Joulin, Gabriel Synnaeve, Jakob Verbeek, Hervé Jégou
2023	—	`conf`	Task-aware Retrieval with Instructions. ACL (Findings) Akari Asai, Timo Schick, Patrick Lewis, Xilun Chen, Gautier Izacard, Sebastian Riedel, Hannaneh Hajishirzi, Wen-tau Yih
2022	J	`jnl`	EditEval: An Instruction-Based Benchmark for Text Improvements. CoRR Jane Dwivedi-Yu, Timo Schick, Zhengbao Jiang, Maria Lomeli, Patrick Lewis, Gautier Izacard, Edouard Grave, Sebastian Riedel, Fabio Petroni
2022	J	`jnl`	Few-shot Learning with Retrieval Augmented Language Models. CoRR Gautier Izacard, Patrick Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, Edouard Grave
2022	J	`jnl`	Improving Wikipedia Verifiability with AI. CoRR Fabio Petroni, Samuel Broscheit, Aleksandra Piktus, Patrick Lewis, Gautier Izacard, Lucas Hosseini, Jane Dwivedi-Yu, Maria Lomeli, Timo Schick, Pierre-Emmanuel Mazaré, Armand Joulin, Edouard Grave, Sebastian Riedel
2022	J	`jnl`	PEER: A Collaborative Language Model. CoRR Timo Schick, Jane Dwivedi-Yu, Zhengbao Jiang, Fabio Petroni, Patrick Lewis, Gautier Izacard, Qingfei You, Christoforos Nalmpantis, Edouard Grave, Sebastian Riedel
2022	J	`jnl`	Task-aware Retrieval with Instructions. CoRR Akari Asai, Timo Schick, Patrick Lewis, Xilun Chen, Gautier Izacard, Sebastian Riedel, Hannaneh Hajishirzi, Wen-tau Yih
2022	J	`jnl`	Unsupervised Dense Information Retrieval with Contrastive Learning. Trans. Mach. Learn. Res. Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, Edouard Grave
2021	J	`jnl`	Are Large-scale Datasets Necessary for Self-Supervised Pre-training? CoRR Alaaeldin El-Nouby, Gautier Izacard, Hugo Touvron, Ivan Laptev, Hervé Jégou, Edouard Grave
2021	A*	`conf`	Autoregressive Entity Retrieval. ICLR Nicola De Cao, Gautier Izacard, Sebastian Riedel, Fabio Petroni
2021	A*	`conf`	Distilling Knowledge from Reader to Retriever for Question Answering. ICLR Gautier Izacard, Edouard Grave
2021	A	`conf`	Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering. EACL Gautier Izacard, Edouard Grave
2021	J	`jnl`	NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned. CoRR Sewon Min, Jordan L. Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Sejr Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih
2021	J	`jnl`	The Web Is Your Oyster - Knowledge-Intensive NLP against a Very Large Web Corpus. CoRR Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Dmytro Okhonko, Samuel Broscheit, Gautier Izacard, Patrick Lewis, Barlas Oguz, Edouard Grave, Wen-tau Yih, Sebastian Riedel
2021	J	`jnl`	Towards Unsupervised Dense Information Retrieval with Contrastive Learning. CoRR Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, Edouard Grave
2020	J	`jnl`	A Memory Efficient Baseline for Open Domain Question Answering. CoRR Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Sebastian Riedel, Edouard Grave
2020	J	`jnl`	Autoregressive Entity Retrieval. CoRR Nicola De Cao, Gautier Izacard, Sebastian Riedel, Fabio Petroni
2020	J	`jnl`	Distilling Knowledge from Reader to Retriever for Question Answering. CoRR Gautier Izacard, Edouard Grave
2020	J	`jnl`	Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering. CoRR Gautier Izacard, Edouard Grave
2020	—	`conf`	NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned. NeurIPS (Competition and Demos) Sewon Min, Jordan L. Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Sejr Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih
2019	Misc	`conf`	A Learning-based Framework for Line-spectra Super-resolution. ICASSP Gautier Izacard, Brett Bernstein, Carlos Fernandez-Granda
2019	A*	`conf`	Data-driven Estimation of Sinusoid Frequencies. NeurIPS Gautier Izacard, Sreyas Mohan, Carlos Fernandez-Granda
2019	J	`jnl`	Data-driven Estimation of Sinusoid Frequencies. CoRR Gautier Izacard, Sreyas Mohan, Carlos Fernandez-Granda
2018	J	`jnl`	A Learning-Based Framework for Line-Spectra Super-resolution. CoRR Gautier Izacard, Brett Bernstein, Carlos Fernandez-Granda
2018	A	`conf`	A new analysis method for evolutionary optimization of dynamic and noisy objective functions. GECCO Raphaël Dang-Nhu, Thibault Dardinier, Benjamin Doerr, Gautier Izacard, Dorian Nogneng

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.