← Authors

Yann LeCun

84 papers · 2007–2025 · 14 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (10) 🐝 Cross-Pollinator (8) 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (18) 🌍 Conference Polyglot (14) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (8) 🏠 Conference Loyalist (21) 🌱 Topic Pioneer πŸ”¬ Deep Specialist (19) 🧬 Topic Evolution πŸ† Keyword Champion πŸ‘‘ Triple Crown 🀝 Dynamic Duo (10) πŸ’Ž Century Club (84) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer ⚑ Prolific Year (10) πŸ”₯ Unstoppable (14) ❓ The Questioner πŸ—ƒοΈ Keyword Collector (279)

Conferences

NIPS (21) ICML (17) ICLR (14) CVPR (11) ICCV (6) AISTATS (3) ECCV (3) JMLR (3) ACL (1) COLT (1) EACL (1) EMNLP (1) NAACL (1) WACV (1)

Top co-authors

Randall Balestriero (10) Ravid Shwartz-Ziv (8) Yubei Chen (6) Shengbang Tong (5) Saining Xie (5) Amir Bar (5) Laurent Najman (4) Quentin Garrido (4) Zhuang Liu (4) Ishan Misra (4)

Keywords

representation learning (15) self-supervised learning (15) convolutional neural network (6) convolutional network (6) multimodal learning (5) deep learning (5) contrastive learning (5) large language model (4) recurrent neural network (4) neural network (3) loss surface (3) stochastic gradient descent (3) unsupervised learning (3) data augmentation (3) model architecture (3) vision language model (3) multimodal large language model (3) model compression (2) unsupervised feature learning (2) semantic segmentation (2)

Papers

Navigation World Models CVPR 2025
RoboPEPP: Vision-Based Robot Pose and Joint Angle Estimation through Embedding Predictive Pre-Training CVPR 2025
Transformers without Normalization CVPR 2025
Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning ICLR 2025
URLOST: Unsupervised Representation Learning without Stationarity or Topology ICLR 2025
Scaling Language-Free Visual Representation Learning ICCV 2025
DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning ICML 2025
Layer by Layer: Uncovering Hidden Representations in Language Models ICML 2025
Forgotten Polygons: Multimodal Large Language Models are Shape-Blind ACL 2025
MetaMorph: Multimodal Understanding and Generation via Instruction Tuning ICCV 2025
Training compute-optimal transformer encoder models EMNLP 2025
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization AISTATS 2025
Rate-In: Information-Driven Adaptive Dropout Rates for Improved Inference-Time Uncertainty Estimation CVPR 2025
LiveBench: A Challenging, Contamination-Limited LLM Benchmark ICLR 2025
Hierarchical World Models as Visual Whole-Body Humanoid Controllers ICLR 2025
$\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs ICLR 2025
PooDLe🐩: Pooled and dense self-supervised learning from naturalistic videos ICLR 2025
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs CVPR 2024
Stochastic positional embeddings improve masked image modeling ICML 2024
How Learning by Reconstruction Produces Uninformative Features For Perception ICML 2024
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning ICLR 2024
Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning NIPS 2024
G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering NIPS 2024
EgoPet: Egomotion and Interaction Data from an Animal's Perspective ECCV 2024
The Entropy Enigma: Success and Failure of Entropy Minimization ICML 2024
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs NIPS 2024
GAIA: a benchmark for General AI Assistants ICLR 2024
Compact and Optimal Deep Learning With Recurrent Parameter Generators WACV 2023
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations NIPS 2023
An Information Theory Perspective on Variance-Invariance-Covariance Regularization NIPS 2023
Reverse Engineering Self-Supervised Learning NIPS 2023
Self-Supervised Learning From Images With a Joint-Embedding Predictive Architecture CVPR 2023
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need ICCV 2023
On the duality between contrastive and non-contrastive self-supervised learning ICLR 2023
Minimalistic Unsupervised Representation Learning with the Sparse Manifold Transform ICLR 2023
The SSL Interplay: Augmentations, Inductive Bias, and Generalization ICML 2023
RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank ICML 2023
Self-supervised learning of Split Invariant Equivariant representations ICML 2023
A Generalization of ViT/MLP-Mixer to Graphs ICML 2023
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors NIPS 2022
Decoupled Contrastive Learning ECCV 2022
The Effects of Regularization and Data Augmentation are Class Dependent NIPS 2022
VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning ICLR 2022
Understanding Dimensional Collapse in Contrastive Self-supervised Learning ICLR 2022
projUNN: efficient method for training deep networks with unitary matrices NIPS 2022
A Data-Augmentation Is Worth A Thousand Samples: Analytical Moments And Sampling-Free Training NIPS 2022
Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone NIPS 2022
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods NIPS 2022
VICRegL: Self-Supervised Learning of Local Visual Features NIPS 2022
MDETR - Modulated Detection for End-to-End Multi-Modal Understanding ICCV 2021
Transformer visualization via dictionary learning: contextualized embedding as a linear superposition of transformer factors NAACL 2021
Barlow Twins: Self-Supervised Learning via Redundancy Reduction ICML 2021
Implicit Rank-Minimizing Autoencoder NIPS 2020
Unsupervised Image Matching and Object Discovery as Optimization CVPR 2019
Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic ICLR 2019
The role of over-parametrization in generalization of neural networks ICLR 2019
Predicting Future Instance Segmentation by Forecasting Convolutional Features ECCV 2018
GLoMo: Unsupervised Learning of Transferable Relational Graphs NIPS 2018
Comparing Dynamics: Deep Neural Networks versus Glassy Systems ICML 2018
Adversarially Regularized Autoencoders ICML 2018
A Closer Look at Spatiotemporal Convolutions for Action Recognition CVPR 2018
Very Deep Convolutional Networks for Text Classification EACL 2017
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs ICML 2017
Predicting Deeper Into the Future of Semantic Segmentation ICCV 2017
Recurrent Orthogonal Networks and Long-Memory Tasks ICML 2016
Binary embeddings with structured hashed projections ICML 2016
Disentangling factors of variation in deep representation using adversarial training NIPS 2016
Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches JMLR 2016
Character-level Convolutional Networks for Text Classification NIPS 2015
Unsupervised Learning of Spatiotemporally Coherent Metrics ICCV 2015
Learning to Linearize Under Uncertainty NIPS 2015
Deep learning with Elastic Averaging SGD NIPS 2015
The Loss Surfaces of Multilayer Networks AISTATS 2015
Open Problem: The landscape of the loss surfaces of multilayer networks COLT 2015
Computing the Stereo Matching Cost With a Convolutional Neural Network CVPR 2015
Efficient Object Localization Using Convolutional Networks CVPR 2015
Convolutional Nets and Watershed Cuts for Real-Time Semantic Labeling of RGBD Videos JMLR 2014
Signal recovery from Pooling Representations ICML 2014
Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation NIPS 2014
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation NIPS 2014
No more pesky learning rates ICML 2013
Pedestrian Detection with Unsupervised Multi-stage Feature Learning CVPR 2013
Deep Learning Made Easier by Linear Transformations in Perceptrons AISTATS 2012
The Need for Open Source Software in Machine Learning JMLR 2007