Quentin Garrido

According to our database, Quentin Garrido authored at least 21 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Interpreting Physics in Video World Models.

Sonia Joseph, Quentin Garrido, Randall Balestriero, Matthew Kowal, Thomas Fel, Shahab Bakhtiari, Blake A. Richards, Mike Rabbat

CoRR, February, 2026

A Lightweight Library for Energy-Based Joint-Embedding Predictive Architectures.

Basile Terver, Randall Balestriero, Megi Dervishi, David Fan, Quentin Garrido, Tushar Nagarajan, Koustuv Sinha, Wancong Zhang, Mike Rabbat, Yann LeCun, Amir Bar

CoRR, February, 2026

Learning Latent Action World Models In The Wild.

Quentin Garrido, Tushar Nagarajan, Basile Terver, Nicolas Ballas, Yann LeCun, Michael Rabbat

CoRR, January, 2026

2025

V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning.

Mido Assran, Adrien Bardes, David Fan, Quentin Garrido, Russell Howes, Mojtaba Komeili, Matthew J. Muckley, Ammar Rizvi, Claire Roberts, Koustuv Sinha, Artem Zholus, Sergio Arnaud, Abha Gejji, Ada Martin, Francois Robert Hogan, Daniel Dugas, Piotr Bojanowski, Vasil Khalidov, Patrick Labatut, Francisco Massa, Marc Szafraniec, Kapil Krishnakumar, Yong Li, Xiaodong Ma, Sarath Chandar, Franziska Meier, Yann LeCun, Michael Rabbat, Nicolas Ballas

CoRR, June, 2025

IntPhys 2: Benchmarking Intuitive Physics Understanding In Complex Synthetic Environments.

Florian Bordes, Quentin Garrido, Justine T. Kao, Adina Williams, Michael Rabbat, Emmanuel Dupoux

CoRR, June, 2025

Intuitive physics understanding emerges from self-supervised pretraining on natural videos.

Quentin Garrido, Nicolas Ballas, Mahmoud Assran, Adrien Bardes, Laurent Najman, Michael Rabbat, Emmanuel Dupoux, Yann LeCun

CoRR, February, 2025

Self-supervised learning beyond invariant image representations. (Apprentissage auto-supervisé au-delà de représentations invariantes d'images).

Quentin Garrido

PhD thesis, 2025

A Shortcut-aware Video-QA Benchmark for Physical Understanding via Minimal Video Pairs.

Benno Krojer, Mojtaba Komeili, Candace Ross, Quentin Garrido, Koustuv Sinha, Nicolas Ballas, Mido Assran

Trans. Mach. Learn. Res., 2025

2024

Revisiting Feature Prediction for Learning Visual Representations from Video.

Adrien Bardes, Quentin Garrido, Jean Ponce, Xinlei Chen, Michael Rabbat, Yann LeCun, Mido Assran, Nicolas Ballas

Trans. Mach. Learn. Res., 2024

An Introduction to Vision-Language Modeling.

Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay, Alexander C. Li, Adrien Bardes, Suzanne Petryk, Oscar Mañas, Zhiqiu Lin, Anas Mahmoud, Bargav Jayaraman, Mark Ibrahim, Melissa Hall, Yunyang Xiong, Jonathan Lebensold, Candace Ross, Srihari Jayakumar, Chuan Guo, Diane Bouchacourt, Haider Al-Tahan, Karthik Padthe, Vasu Sharma, Hu Xu, Xiaoqing Ellen Tan, Megan Richards, Samuel Lavoie, Pietro Astolfi, Reyhane Askari Hemmat, Jun Chen, Kushal Tirumala, Rim Assouel, Mazda Moayeri, Arjang Talattof, Kamalika Chaudhuri, Zechun Liu, Xilun Chen, Quentin Garrido, Karen Ullrich, Aishwarya Agrawal, Kate Saenko, Asli Celikyilmaz, Vikas Chandra

CoRR, 2024

Learning and Leveraging World Models in Visual Representation Learning.

Quentin Garrido, Mahmoud Assran, Nicolas Ballas, Adrien Bardes, Laurent Najman, Yann LeCun

CoRR, 2024

UniBench: Visual Reasoning Requires Rethinking Vision-Language Beyond Scaling.

Haider Al-Tahan, Quentin Garrido, Randall Balestriero, Diane Bouchacourt, Caner Hazirbas, Mark Ibrahim

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

The Robustness Limits of SoTA Vision Models to Natural Variation.

Mark Ibrahim, Quentin Garrido, Ari S. Morcos, Diane Bouchacourt

Trans. Mach. Learn. Res., 2023

Guillotine Regularization: Why removing layers is needed to improve generalization in Self-Supervised Learning.

Florian Bordes, Randall Balestriero, Quentin Garrido, Adrien Bardes, Pascal Vincent

Trans. Mach. Learn. Res., 2023

A Cookbook of Self-Supervised Learning.

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

CoRR, 2023

Self-Supervised Learning with Lie Symmetries for Partial Differential Equations.

Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak T. Kiani

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Self-supervised learning of Split Invariant Equivariant representations.

Quentin Garrido, Laurent Najman, Yann LeCun

Proceedings of the International Conference on Machine Learning, 2023

RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank.

Quentin Garrido, Randall Balestriero, Laurent Najman, Yann LeCun

Proceedings of the International Conference on Machine Learning, 2023

On the duality between contrastive and non-contrastive self-supervised learning.

Quentin Garrido, Yubei Chen, Adrien Bardes, Laurent Najman, Yann LeCun

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Guillotine Regularization: Improving Deep Networks Generalization by Removing their Head.

Florian Bordes, Randall Balestriero, Quentin Garrido, Adrien Bardes, Pascal Vincent

CoRR, 2022

Visualizing hierarchies in scRNA-seq data using a density tree-biased autoencoder.

Quentin Garrido, Sebastian Damrich, Alexander Jäger, Dario Cerletti, Manfred Claassen, Laurent Najman, Fred A. Hamprecht

Bioinform., 2022