Pierre Stock - RankMe

30 papers A* 6Journal 19Unranked 4

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	LLM-QAT: Data-Free Quantization Aware Training for Large Language Models. ACL (Findings) Zechun Liu, Barlas Oguz, Changsheng Zhao, Ernie Chang, Pierre Stock, Yashar Mehdad, Yangyang Shi, Raghuraman Krishnamoorthi, Vikas Chandra
2024	J	`jnl`	Mixtral of Experts. CoRR Albert Q. Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de Las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Sandeep Subramanian, Sophia Yang, Szymon Antoniak, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed
2024	J	`jnl`	Pixtral 12B. CoRR Pravesh Agrawal, Szymon Antoniak, Emma Bou Hanna, Baptiste Bout, Devendra Singh Chaplot, Jessica Chudnovsky, Diogo Costa, Baudouin De Monicault, Saurabh Garg, Théophile Gervet, Soham Ghosh, Amélie Héliou, Paul Jacob, Albert Q. Jiang, Kartik Khandelwal, Timothée Lacroix, Guillaume Lample, Diego de Las Casas, Thibaut Lavril, Teven Le Scao, Andy Lo, William Marshall, Louis Martin, Arthur Mensch, Pavankumar Muddireddy, Valera Nemychnikova, Marie Pellat, Patrick von Platen, Nikhil Raghuraman, Baptiste Rozière, Alexandre Sablayrolles, Lucile Saulnier, Romain Sauvestre, Wendy Shang, Roman Soletskyi, Lawrence Stewart, Pierre Stock, Joachim Studnia, Sandeep Subramanian, Sagar Vaze, Thomas Wang, Sophia Yang
2023	A*	`conf`	CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning. ICLR Samuel Maddock, Alexandre Sablayrolles, Pierre Stock
2023	J	`jnl`	EXACT: Extensive Attack for Split Learning. CoRR Xinchi Qiu, Ilias Leontiadis, Luca Melis, Alexandre Sablayrolles, Pierre Stock
2023	J	`jnl`	Green Federated Learning. CoRR Ashkan Yousefpour, Shen Guo, Ashish Shenoy, Sayan Ghosh, Pierre Stock, Kiwan Maeng, Schalk-Willem Krüger, Michael G. Rabbat, Carole-Jean Wu, Ilya Mironov
2023	J	`jnl`	LLM-QAT: Data-Free Quantization Aware Training for Large Language Models. CoRR Zechun Liu, Barlas Oguz, Changsheng Zhao, Ernie Chang, Pierre Stock, Yashar Mehdad, Yangyang Shi, Raghuraman Krishnamoorthi, Vikas Chandra
2023	J	`jnl`	Mistral 7B. CoRR Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de Las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed
2023	A*	`conf`	Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design. ICML Chuan Guo, Kamalika Chaudhuri, Pierre Stock, Michael G. Rabbat
2023	J	`jnl`	Reconciling Security and Communication Efficiency in Federated Learning. IEEE Data Eng. Bull. Karthik Prasad, Sayan Ghosh, Graham Cormode, Ilya Mironov, Ashkan Yousefpour, Pierre Stock
2023	A*	`conf`	TAN Without a Burn: Scaling Laws of DP-SGD. ICML Tom Sander, Pierre Stock, Alexandre Sablayrolles
2022	J	`jnl`	CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning. CoRR Samuel Maddock, Alexandre Sablayrolles, Pierre Stock
2022	J	`jnl`	Defending against Reconstruction Attacks with Rényi Differential Privacy. CoRR Pierre Stock, Igor Shilov, Ilya Mironov, Alexandre Sablayrolles
2022	J	`jnl`	Reconciling Security and Communication Efficiency in Federated Learning. CoRR Karthik Prasad, Sayan Ghosh, Graham Cormode, Ilya Mironov, Ashkan Yousefpour, Pierre Stock
2022	J	`jnl`	TAN without a burn: Scaling Laws of DP-SGD. CoRR Tom Sander, Pierre Stock, Alexandre Sablayrolles
2022	J	`jnl`	The Interpolated MVU Mechanism For Communication-efficient Private Federated Learning. CoRR Chuan Guo, Kamalika Chaudhuri, Pierre Stock, Mike Rabbat
2021	J	`jnl`	An Embedding of ReLU Networks and an Analysis of their Identifiability. CoRR Pierre Stock, Rémi Gribonval
2021	—	`—`	Efficiency and Redundancy in Deep Learning Models: Theoretical Considerations and Practical Applications. (Efficience et redondance dans les modèles d'apprentissage profond : considérations théoriques et applications pratiques). Pierre Stock
2021	A*	`conf`	LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference. ICCV Benjamin Graham, Alaaeldin El-Nouby, Hugo Touvron, Pierre Stock, Armand Joulin, Hervé Jégou, Matthijs Douze
2021	J	`jnl`	LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference. CoRR Benjamin Graham, Alaaeldin El-Nouby, Hugo Touvron, Pierre Stock, Armand Joulin, Hervé Jégou, Matthijs Douze
2021	—	`conf`	Low Bandwidth Video-Chat Compression Using Deep Generative Models. CVPR Workshops Maxime Oquab, Pierre Stock, Daniel Haziza, Tao Xu, Peizhao Zhang, Onur Celebi, Yana Hasson, Patrick Labatut, Bobo Bose-Kolanu, Thibault Peyronel, Camille Couprie
2021	A*	`conf`	Training with Quantization Noise for Extreme Model Compression. ICLR Pierre Stock, Angela Fan, Benjamin Graham, Edouard Grave, Rémi Gribonval, Hervé Jégou, Armand Joulin
2020	A*	`conf`	And the Bit Goes Down: Revisiting the Quantization of Neural Networks. ICLR Pierre Stock, Armand Joulin, Rémi Gribonval, Benjamin Graham, Hervé Jégou
2020	J	`jnl`	Low Bandwidth Video-Chat Compression using Deep Generative Models. CoRR Maxime Oquab, Pierre Stock, Oran Gafni, Daniel Haziza, Tao Xu, Peizhao Zhang, Onur Celebi, Yana Hasson, Patrick Labatut, Bobo Bose-Kolanu, Thibault Peyronel, Camille Couprie
2020	J	`jnl`	Training with Quantization Noise for Extreme Model Compression. CoRR Angela Fan, Pierre Stock, Benjamin Graham, Edouard Grave, Rémi Gribonval, Hervé Jégou, Armand Joulin
2019	J	`jnl`	And the Bit Goes Down: Revisiting the Quantization of Neural Networks. CoRR Pierre Stock, Armand Joulin, Rémi Gribonval, Benjamin Graham, Hervé Jégou
2019	—	`conf`	Equi-normalization of Neural Networks. ICLR (Poster) Pierre Stock, Benjamin Graham, Rémi Gribonval, Hervé Jégou
2019	J	`jnl`	Equi-normalization of Neural Networks. CoRR Pierre Stock, Benjamin Graham, Rémi Gribonval, Hervé Jégou
2018	—	`conf`	ConvNets and ImageNet Beyond Accuracy: Understanding Mistakes and Uncovering Biases. ECCV (6) Pierre Stock, Moustapha Cissé
2017	J	`jnl`	ConvNets and ImageNet Beyond Accuracy: Explanations, Bias Detection, Adversarial Examples and Model Criticism. CoRR Pierre Stock, Moustapha Cissé