On Training in Imagination
Fuente:
arXiv
Saved in:
| Main Authors: | Timor, Nadav, Shwartz-Ziv, Ravid, Goldblum, Micah, LeCun, Yann, Harel, David |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Just How Flexible are Neural Networks in Practice?
by: Shwartz-Ziv, Ravid, et al.
Published: (2024)
by: Shwartz-Ziv, Ravid, et al.
Published: (2024)
Does Representation Matter? Exploring Intermediate Layers in Large Language Models
by: Skean, Oscar, et al.
Published: (2024)
by: Skean, Oscar, et al.
Published: (2024)
Variance-Covariance Regularization Improves Representation Learning
by: Zhu, Jiachen, et al.
Published: (2023)
by: Zhu, Jiachen, et al.
Published: (2023)
Video Representation Learning with Joint-Embedding Predictive Architectures
by: Drozdov, Katrina, et al.
Published: (2024)
by: Drozdov, Katrina, et al.
Published: (2024)
Rate-In: Information-Driven Adaptive Dropout Rates for Improved Inference-Time Uncertainty Estimation
by: Zeevi, Tal, et al.
Published: (2024)
by: Zeevi, Tal, et al.
Published: (2024)
Closing the Train-Test Gap in World Models for Gradient-Based Planning
by: Parthasarathy, Arjun, et al.
Published: (2025)
by: Parthasarathy, Arjun, et al.
Published: (2025)
Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning
by: Arefin, Md Rifat, et al.
Published: (2024)
by: Arefin, Md Rifat, et al.
Published: (2024)
JEPA as a Neural Tokenizer: Learning Robust Speech Representations with Density Adaptive Attention
by: Ioannides, Georgios, et al.
Published: (2025)
by: Ioannides, Georgios, et al.
Published: (2025)
Layer by Layer: Uncovering Hidden Representations in Language Models
by: Skean, Oscar, et al.
Published: (2025)
by: Skean, Oscar, et al.
Published: (2025)
Attention Sinks and Compression Valleys in LLMs are Two Sides of the Same Coin
by: Queipo-de-Llano, Enrique, et al.
Published: (2025)
by: Queipo-de-Llano, Enrique, et al.
Published: (2025)
AI Must Embrace Specialization via Superhuman Adaptable Intelligence
by: Goldfeder, Judah, et al.
Published: (2026)
by: Goldfeder, Judah, et al.
Published: (2026)
The Entropy Enigma: Success and Failure of Entropy Minimization
by: Press, Ori, et al.
Published: (2024)
by: Press, Ori, et al.
Published: (2024)
Soft Clustering Anchors for Self-Supervised Speech Representation Learning in Joint Embedding Prediction Architectures
by: Ioannides, Georgios, et al.
Published: (2026)
by: Ioannides, Georgios, et al.
Published: (2026)
Learning to Compress: Local Rank and Information Compression in Deep Neural Networks
by: Patel, Niket, et al.
Published: (2024)
by: Patel, Niket, et al.
Published: (2024)
Fast and Exact Enumeration of Deep Networks Partitions Regions
by: Balestriero, Randall, et al.
Published: (2024)
by: Balestriero, Randall, et al.
Published: (2024)
From Tokens to Thoughts: How LLMs and Humans Trade Compression for Meaning
by: Shani, Chen, et al.
Published: (2025)
by: Shani, Chen, et al.
Published: (2025)
Introduction to Latent Variable Energy-Based Models: A Path Towards Autonomous Machine Intelligence
by: Dawid, Anna, et al.
Published: (2023)
by: Dawid, Anna, et al.
Published: (2023)
LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics
by: Balestriero, Randall, et al.
Published: (2025)
by: Balestriero, Randall, et al.
Published: (2025)
Learning by Reconstruction Produces Uninformative Features For Perception
by: Balestriero, Randall, et al.
Published: (2024)
by: Balestriero, Randall, et al.
Published: (2024)
Semantic Tube Prediction: Beating LLM Data Efficiency with JEPA
by: Huang, Hai, et al.
Published: (2026)
by: Huang, Hai, et al.
Published: (2026)
Variance Covariance Regularization Enforces Pairwise Independence in Self-Supervised Representations
by: Mialon, Grégoire, et al.
Published: (2022)
by: Mialon, Grégoire, et al.
Published: (2022)
Out-of-Vocabulary Sampling Boosts Speculative Decoding
by: Timor, Nadav, et al.
Published: (2025)
by: Timor, Nadav, et al.
Published: (2025)
An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization
by: Shwartz-Ziv, Ravid, et al.
Published: (2023)
by: Shwartz-Ziv, Ravid, et al.
Published: (2023)
A hierarchical loss and its problems when classifying non-hierarchically
by: Wu, Cinna, et al.
Published: (2017)
by: Wu, Cinna, et al.
Published: (2017)
LiveBench: A Challenging, Contamination-Limited LLM Benchmark
by: White, Colin, et al.
Published: (2024)
by: White, Colin, et al.
Published: (2024)
Antislop: A Comprehensive Framework for Identifying and Eliminating Repetitive Patterns in Language Models
by: Paech, Samuel, et al.
Published: (2025)
by: Paech, Samuel, et al.
Published: (2025)
NdLinear: Preserving Multi-Dimensional Structure for Parameter-Efficient Neural Networks
by: Reneau, Alex, et al.
Published: (2025)
by: Reneau, Alex, et al.
Published: (2025)
Layer Importance for Mathematical Reasoning is Forged in Pre-Training and Invariant after Post-Training
by: Nepal, Aadim, et al.
Published: (2025)
by: Nepal, Aadim, et al.
Published: (2025)
URLOST: Unsupervised Representation Learning without Stationarity or Topology
by: Yun, Zeyu, et al.
Published: (2023)
by: Yun, Zeyu, et al.
Published: (2023)
When Attention Collapses: How Degenerate Layers in LLMs Enable Smaller, Stronger Models
by: Sanyal, Sunny, et al.
Published: (2024)
by: Sanyal, Sunny, et al.
Published: (2024)
Blockwise Self-Supervised Learning at Scale
by: Siddiqui, Shoaib Ahmed, et al.
Published: (2023)
by: Siddiqui, Shoaib Ahmed, et al.
Published: (2023)
Gaussian Embeddings: How JEPAs Secretly Learn Your Data Density
by: Balestriero, Randall, et al.
Published: (2025)
by: Balestriero, Randall, et al.
Published: (2025)
Parallel Stochastic Gradient-Based Planning for World Models
by: Psenka, Michael, et al.
Published: (2026)
by: Psenka, Michael, et al.
Published: (2026)
Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations
by: Schaeffer, Rylan, et al.
Published: (2024)
by: Schaeffer, Rylan, et al.
Published: (2024)
Implicit Regularization Towards Rank Minimization in ReLU Networks
by: Timor, Nadav, et al.
Published: (2022)
by: Timor, Nadav, et al.
Published: (2022)
LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels
by: Maes, Lucas, et al.
Published: (2026)
by: Maes, Lucas, et al.
Published: (2026)
Value-guided action planning with JEPA world models
by: Destrade, Matthieu, et al.
Published: (2025)
by: Destrade, Matthieu, et al.
Published: (2025)
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning
by: He, Xiaoxin, et al.
Published: (2023)
by: He, Xiaoxin, et al.
Published: (2023)
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation
by: Denton, Remi, et al.
Published: (2014)
by: Denton, Remi, et al.
Published: (2014)
Light-weight probing of unsupervised representations for Reinforcement Learning
by: Zhang, Wancong, et al.
Published: (2022)
by: Zhang, Wancong, et al.
Published: (2022)
Similar Items
-
Just How Flexible are Neural Networks in Practice?
by: Shwartz-Ziv, Ravid, et al.
Published: (2024) -
Does Representation Matter? Exploring Intermediate Layers in Large Language Models
by: Skean, Oscar, et al.
Published: (2024) -
Variance-Covariance Regularization Improves Representation Learning
by: Zhu, Jiachen, et al.
Published: (2023) -
Video Representation Learning with Joint-Embedding Predictive Architectures
by: Drozdov, Katrina, et al.
Published: (2024) -
Rate-In: Information-Driven Adaptive Dropout Rates for Improved Inference-Time Uncertainty Estimation
by: Zeevi, Tal, et al.
Published: (2024)