Yann LeCun

Publication Activity (10 Years)

Years Active: 1988-2024
Publications (10 Years): 200

Top Venues

CoRR

NeurIPS

ICML

ICLR

Publications

Colin White, Samuel Dooley, Manley Roberts, Arka Pal, Benjamin Feuer, Siddhartha Jain, Ravid Shwartz-Ziv, Neel Jain, Khalid Saifullah, Siddartha Naidu, Chinmay Hegde, Yann LeCun, Tom Goldstein, Willie Neiswanger, Micah Goldblum
LiveBench: A Challenging, Contamination-Free LLM Benchmark. CoRR (2024)
Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun
𝕏-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs. CoRR (2024)
Li Liu, Timothy M. Hospedales, Yann LeCun, Mingsheng Long, Jiebo Luo, Wanli Ouyang, Matti Pietikäinen, Tinne Tuytelaars
Editorial: Learning With Fewer Labels in Computer Vision. IEEE Trans. Pattern Anal. Mach. Intell. 46 (3) (2024)
Ravid Shwartz-Ziv, Yann LeCun
To Compress or Not to Compress - Self-Supervised Learning and Information Theory: A Review. Entropy 26 (3) (2024)
Amir Bar, Arya Bakhtiar, Danny Tran, Antonio Loquercio, Jathushan Rajasegaran, Yann LeCun, Amir Globerson, Trevor Darrell
EgoPet: Egomotion and Interaction Data from an Animal's Perspective. CoRR (2024)
Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi Ma, Yann LeCun, Saining Xie
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs. CoRR (2024)
Théo Moutakanni, Piotr Bojanowski, Guillaume Chassagnon, Céline Hudelot, Armand Joulin, Yann LeCun, Matthew Muckley, Maxime Oquab, Marie-Pierre Revel, Maria Vakalopoulou
Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learning. CoRR (2024)
Shoaib Ahmed Siddiqui, David Krueger, Yann LeCun, Stéphane Deny
Blockwise Self-Supervised Learning at Scale. Trans. Mach. Learn. Res. 2024 (2024)
Adrien Basdevant, Camille François, Victor Storchan, Kevin Bankston, Ayah Bdeir, Brian Behlendorf, Mérouane Debbah, Sayash Kapoor, Yann LeCun, Mark Surman, Helen King-Turvey, Nathan Lambert, Stefano Maffulli, Nik Marda, Govind Shivkumar, Justine Tunney
Towards a Framework for Openness in Foundation Models: Proceedings from the Columbia Convening on Openness in Artificial Intelligence. CoRR (2024)
Randall Balestriero, Yann LeCun
Fast and Exact Enumeration of Deep Networks Partitions Regions. CoRR (2024)
Yuexiang Zhai, Hao Bai, Zipeng Lin, Jiayi Pan, Shengbang Tong, Yifei Zhou, Alane Suhr, Saining Xie, Yann LeCun, Yi Ma, Sergey Levine
Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning. CoRR (2024)
Adrien Bardes, Quentin Garrido, Jean Ponce, Xinlei Chen, Michael G. Rabbat, Yann LeCun, Mahmoud Assran, Nicolas Ballas
Revisiting Feature Prediction for Learning Visual Representations from Video. CoRR (2024)
Shengbang Tong, Ellis Brown, Penghao Wu, Sanghyun Woo, Manoj Middepogu, Sai Charitha Akula, Jihan Yang, Shusheng Yang, Adithya Iyer, Xichen Pan, Austin Wang, Rob Fergus, Yann LeCun, Saining Xie
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs. CoRR (2024)
Nicklas Hansen, Jyothir S. V, Vlad Sobal, Yann LeCun, Xiaolong Wang, Hao Su
Hierarchical World Models as Visual Whole-Body Humanoid Controllers. CoRR (2024)
Grégoire Mialon, Clémentine Fourrier, Thomas Wolf, Yann LeCun, Thomas Scialom
GAIA: a benchmark for General AI Assistants. ICLR (2024)
Ravid Shwartz-Ziv, Micah Goldblum, Arpit Bansal, C. Bayan Bruss, Yann LeCun, Andrew Gordon Wilson
Just How Flexible are Neural Networks in Practice? CoRR (2024)
Xiaoxin He, Xavier Bresson, Thomas Laurent, Adam Perold, Yann LeCun, Bryan Hooi
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning. ICLR (2024)
Ori Press, Ravid Shwartz-Ziv, Yann LeCun, Matthias Bethge
The Entropy Enigma: Success and Failure of Entropy Minimization. CoRR (2024)
Randall Balestriero, Yann LeCun
Learning by Reconstruction Produces Uninformative Features For Perception. CoRR (2024)
Rylan Schaeffer, Victor Lecomte, Dhruv Bhandarkar Pai, Andres Carranza, Berivan Isik, Alyssa Unell, Mikail Khona, Thomas E. Yerxa, Yann LeCun, SueYeon Chung, Andrey Gromov, Ravid Shwartz-Ziv, Sanmi Koyejo
Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations. CoRR (2024)
Quentin Garrido, Mahmoud Assran, Nicolas Ballas, Adrien Bardes, Laurent Najman, Yann LeCun
Learning and Leveraging World Models in Visual Representation Learning. CoRR (2024)
Xiaoxin He, Yijun Tian, Yifei Sun, Nitesh V. Chawla, Thomas Laurent, Yann LeCun, Xavier Bresson, Bryan Hooi
G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering. CoRR (2024)
Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti, Shai Dekel, Yann LeCun
Reverse Engineering Self-Supervised Learning. NeurIPS (2023)
Ravid Shwartz-Ziv, Yann LeCun
To Compress or Not to Compress - Self-Supervised Learning and Information Theory: A Review. CoRR (2023)
Shraman Pramanick, Li Jing, Sayan Nag, Jiachen Zhu, Hardik Shah, Yann LeCun, Rama Chellappa
VoLTA: Vision-Language Transformer with Weakly-Supervised Local-Feature Alignment. Trans. Mach. Learn. Res. 2023 (2023)
Ravid Shwartz-Ziv, Randall Balestriero, Kenji Kawaguchi, Tim G. J. Rudner, Yann LeCun
An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization. CoRR (2023)
Adrien Bardes, Jean Ponce, Yann LeCun
MC-JEPA: A Joint-Embedding Predictive Architecture for Self-Supervised Learning of Motion and Content Features. CoRR (2023)
Vivien Cabannes, Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti
The SSL Interplay: Augmentations, Inductive Bias, and Generalization. CoRR (2023)
Quentin Garrido, Randall Balestriero, Laurent Najman, Yann LeCun
RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank. ICML (2023)
Grégoire Mialon, Clémentine Fourrier, Craig Swift, Thomas Wolf, Yann LeCun, Thomas Scialom
GAIA: a benchmark for General AI Assistants. CoRR (2023)
Shengbang Tong, Yubei Chen, Yi Ma, Yann LeCun
EMP-SSL: Towards Self-Supervised Learning in One Training Epoch. CoRR (2023)
Amir Bar, Florian Bordes, Assaf Shocher, Mahmoud Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann LeCun
Predicting masked tokens in stochastic locations improves masked image modeling. CoRR (2023)
Jiayun Wang, Yubei Chen, Stella X. Yu, Brian Cheung, Yann LeCun
Compact and Optimal Deep Learning with Recurrent Parameter Generators. WACV (2023)
Grégoire Mialon, Roberto Dessì, Maria Lomeli, Christoforos Nalmpantis, Ramakanth Pasunuru, Roberta Raileanu, Baptiste Rozière, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, Thomas Scialom
Augmented Language Models: a Survey. CoRR (2023)
Jiachen Zhu, Ravid Shwartz-Ziv, Yubei Chen, Yann LeCun
Variance-Covariance Regularization Improves Representation Learning. CoRR (2023)
Zeyu Yun, Juexiao Zhang, Bruno A. Olshausen, Yann LeCun, Yubei Chen
URLOST: Unsupervised Representation Learning without Stationarity or Topology. CoRR (2023)
Ying Wang, Jonas Pfeiffer, Nicolas Carion, Yann LeCun, Aishwarya Kamath
Adapting Grounded Visual Question Answering Models to Low Resource Languages. CVPR Workshops (2023)
Jyothir S. V, Siddhartha Jalagam, Yann LeCun, Vlad Sobal
Gradient-based Planning with World Models. CoRR (2023)
Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. CoRR (2023)
Grégoire Mialon, Roberto Dessì, Maria Lomeli, Christoforos Nalmpantis, Ramakanth Pasunuru, Roberta Raileanu, Baptiste Rozière, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, Thomas Scialom
Augmented Language Models: a Survey. Trans. Mach. Learn. Res. 2023 (2023)
Vivien Cabannes, Léon Bottou, Yann LeCun, Randall Balestriero
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need. ICCV (2023)
Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti, Shai Dekel, Yann LeCun
Reverse Engineering Self-Supervised Learning. CoRR (2023)
Vivien Cabannes, Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti
The SSL Interplay: Augmentations, Inductive Bias, and Generalization. ICML (2023)
Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak T. Kiani
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations. NeurIPS (2023)
Ravid Shwartz-Ziv, Randall Balestriero, Kenji Kawaguchi, Tim G. J. Rudner, Yann LeCun
An Information Theory Perspective on Variance-Invariance-Covariance Regularization. NeurIPS (2023)
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
A Cookbook of Self-Supervised Learning. CoRR (2023)
Yubei Chen, Zeyu Yun, Yi Ma, Bruno A. Olshausen, Yann LeCun
Minimalistic Unsupervised Representation Learning with the Sparse Manifold Transform. ICLR (2023)
Quentin Garrido, Laurent Najman, Yann LeCun
Self-supervised learning of Split Invariant Equivariant representations. ICML (2023)
Randall Balestriero, Yann LeCun
Police: Provably Optimal Linear Constraint Enforcement For Deep Neural Networks. ICASSP (2023)
Jacob Browning, Yann LeCun
Language, common sense, and the Winograd schema challenge. Artif. Intell. 325 (2023)
Randall Balestriero, Yann LeCun
Fast and Exact Enumeration of Deep Networks Partitions Regions. ICASSP (2023)
Vivien Cabannes, Léon Bottou, Yann LeCun, Randall Balestriero
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need. CoRR (2023)
Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. CVPR (2023)
Yubei Chen, Adrien Bardes, Zengyi Li, Yann LeCun
Bag of Image Patch Embedding Behind the Success of Self-Supervised Learning. Trans. Mach. Learn. Res. 2023 (2023)
Quentin Garrido, Laurent Najman, Yann LeCun
Self-supervised learning of Split Invariant Equivariant representations. CoRR (2023)
Xiaoxin He, Bryan Hooi, Thomas Laurent, Adam Perold, Yann LeCun, Xavier Bresson
A Generalization of ViT/MLP-Mixer to Graphs. ICML (2023)
Shoaib Ahmed Siddiqui, David Krueger, Yann LeCun, Stéphane Deny
Blockwise Self-Supervised Learning at Scale. CoRR (2023)
Anna Dawid, Yann LeCun
Introduction to Latent Variable Energy-Based Models: A Path Towards Autonomous Machine Intelligence. CoRR (2023)
Quentin Garrido, Yubei Chen, Adrien Bardes, Laurent Najman, Yann LeCun
On the duality between contrastive and non-contrastive self-supervised learning. ICLR (2023)
Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak Toussi Kiani
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations. CoRR (2023)
Yubei Chen, Zeyu Yun, Yi Ma, Bruno A. Olshausen, Yann LeCun
Minimalistic Unsupervised Learning with the Sparse Manifold Transform. CoRR (2022)
Randall Balestriero, Léon Bottou, Yann LeCun
The Effects of Regularization and Data Augmentation are Class Dependent. CoRR (2022)
Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian
Understanding Dimensional Collapse in Contrastive Self-supervised Learning. ICLR (2022)
Ravid Shwartz-Ziv, Micah Goldblum, Hossein Souri, Sanyam Kapoor, Chen Zhu, Yann LeCun, Andrew Gordon Wilson
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors. CoRR (2022)
Randall Balestriero, Léon Bottou, Yann LeCun
The Effects of Regularization and Data Augmentation are Class Dependent. NeurIPS (2022)
Katrina Evtimova, Yann LeCun
Sparse Coding with Multi-layer Decoders using Variance Regularization. Trans. Mach. Learn. Res. 2022 (2022)
Bobak Toussi Kiani, Randall Balestriero, Yubei Chen, Seth Lloyd, Yann LeCun
Joint Embedding Self-Supervised Learning in the Kernel Regime. CoRR (2022)
Vlad Sobal, Jyothir S. V, Siddhartha Jalagam, Nicolas Carion, Kyunghyun Cho, Yann LeCun
Joint Embedding Predictive Architectures Focus on Slow Features. CoRR (2022)
Shraman Pramanick, Li Jing, Sayan Nag, Jiachen Zhu, Hardik Shah, Yann LeCun, Rama Chellappa
VoLTA: Vision-Language Transformer with Weakly-Supervised Local-Feature Alignment. CoRR (2022)
Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd
projUNN: efficient method for training deep networks with unitary matrices. NeurIPS (2022)
Quentin Garrido, Randall Balestriero, Laurent Najman, Yann LeCun
RankMe: Assessing the downstream performance of pretrained self-supervised representations by their rank. CoRR (2022)
Zi-Yi Dou, Aishwarya Kamath, Zhe Gan, Pengchuan Zhang, Jianfeng Wang, Linjie Li, Zicheng Liu, Ce Liu, Yann LeCun, Nanyun Peng, Jianfeng Gao, Lijuan Wang
Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone. CoRR (2022)
Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd
projUNN: efficient method for training deep networks with unitary matrices. CoRR (2022)
Zi-Yi Dou, Aishwarya Kamath, Zhe Gan, Pengchuan Zhang, Jianfeng Wang, Linjie Li, Zicheng Liu, Ce Liu, Yann LeCun, Nanyun Peng, Jianfeng Gao, Lijuan Wang
Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone. NeurIPS (2022)
Ravid Shwartz-Ziv, Randall Balestriero, Yann LeCun
What Do We Maximize in Self-Supervised Learning? CoRR (2022)
Randall Balestriero, Ishan Misra, Yann LeCun
A Data-Augmentation Is Worth A Thousand Samples: Exact Quantification From Analytical Augmented Sample Moments. CoRR (2022)
Adrien Bardes, Jean Ponce, Yann LeCun
VICRegL: Self-Supervised Learning of Local Visual Features. CoRR (2022)
Xiaoxin He, Bryan Hooi, Thomas Laurent, Adam Perold, Yann LeCun, Xavier Bresson
A Generalization of ViT/MLP-Mixer to Graphs. CoRR (2022)
Chun-Hsiao Yeh, Cheng-Yao Hong, Yen-Chi Hsu, Tyng-Luh Liu, Yubei Chen, Yann LeCun
Decoupled Contrastive Learning. ECCV (26) (2022)
Adrien Bardes, Jean Ponce, Yann LeCun
VICRegL: Self-Supervised Learning of Local Visual Features. NeurIPS (2022)
Shengbang Tong, Xili Dai, Yubei Chen, Mingyang Li, Zengyi Li, Brent Yi, Yann LeCun, Yi Ma
Unsupervised Learning of Structured Representations via Closed-Loop Transcription. CoRR (2022)
Grégoire Mialon, Randall Balestriero, Yann LeCun
Variance Covariance Regularization Enforces Pairwise Independence in Self-Supervised Representations. CoRR (2022)
Quentin Garrido, Yubei Chen, Adrien Bardes, Laurent Najman, Yann LeCun
On the duality between contrastive and non-contrastive self-supervised learning. CoRR (2022)
Vlad Sobal, Alfredo Canziani, Nicolas Carion, Kyunghyun Cho, Yann LeCun
Separating the World and Ego Models for Self-Driving. CoRR (2022)
Li Jing, Jiachen Zhu, Yann LeCun
Masked Siamese ConvNets. CoRR (2022)
Adrien Bardes, Jean Ponce, Yann LeCun
VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning. ICLR (2022)
Zengyi Li, Yubei Chen, Yann LeCun, Friedrich T. Sommer
Neural Manifold Clustering and Embedding. CoRR (2022)
Randall Balestriero, Ishan Misra, Yann LeCun
A Data-Augmentation Is Worth A Thousand Samples: Analytical Moments And Sampling-Free Training. NeurIPS (2022)
Anthony Zador, Blake A. Richards, Bence Ölveczky, Sean Escola, Yoshua Bengio, Kwabena Boahen, Matthew M. Botvinick, Dmitri B. Chklovskii, Anne Churchland, Claudia Clopath, James DiCarlo, Surya Ganguli, Jeff Hawkins, Konrad P. Körding, Alexei A. Koulakov, Yann LeCun, Timothy P. Lillicrap, Adam H. Marblestone, Bruno A. Olshausen, Alexandre Pouget, Cristina Savin, Terrence J. Sejnowski, Eero P. Simoncelli, Sara A. Solla, David Sussillo, Andreas S. Tolias, Doris Tsao
Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution. CoRR (2022)
Randall Balestriero, Yann LeCun
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods. NeurIPS (2022)
Ravid Shwartz-Ziv, Micah Goldblum, Hossein Souri, Sanyam Kapoor, Chen Zhu, Yann LeCun, Andrew G. Wilson
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors. NeurIPS (2022)
Jiachen Zhu, Rafael M. Moraes, Serkan Karakulak, Vlad Sobol, Alfredo Canziani, Yann LeCun
TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning. CoRR (2022)
Randall Balestriero, Yann LeCun
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods. CoRR (2022)
Randall Balestriero, Yann LeCun
POLICE: Provably Optimal Linear Constraint Enforcement for Deep Neural Networks. CoRR (2022)
Yutaka Matsuo, Yann LeCun, Maneesh Sahani, Doina Precup, David Silver, Masashi Sugiyama, Eiji Uchibe, Jun Morimoto
Deep learning, reinforcement learning, and world models. Neural Networks 152 (2022)
Yubei Chen, Adrien Bardes, Zengyi Li, Yann LeCun
Intra-Instance VICReg: Bag of Self-Supervised Image Patch Embedding. CoRR (2022)
Wancong Zhang, Anthony GX-Chen, Vlad Sobal, Yann LeCun, Nicolas Carion
Light-weight probing of unsupervised representations for Reinforcement Learning. CoRR (2022)
Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, Stéphane Deny
Barlow Twins: Self-Supervised Learning via Redundancy Reduction. CoRR (2021)
Zeyu Yun, Yubei Chen, Bruno A. Olshausen, Yann LeCun
Transformer visualization via dictionary learning: contextualized embedding as a linear superposition of transformer factors. DeeLIO@NAACL-HLT (2021)
Chun-Hsiao Yeh, Cheng-Yao Hong, Yen-Chi Hsu, Tyng-Luh Liu, Yubei Chen, Yann LeCun
Decoupled Contrastive Learning. CoRR (2021)

Yann LeCun.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Yann LeCun