Factorization Regret mediates compositional generalization in latent space

arXiv:2603.27134 · cs.LG · Submitted 2026-03-28 · Read on arXiv

cs.LG

Submitted: 2026-03-28

Updated: 2026-09-27

Terminology

• Embeddings — 35× in this paper · explained in 2 episodes
• Generalization — 30× in this paper · explained in 13 episodes
• Accuracy — 25× in this paper · explained in 1 episode
• Regret — 23× in this paper · explained in 3 episodes
• Factorization Regret — 22× in this paper
• Entanglement — 17× in this paper · explained in 3 episodes
• Latent Space — 13× in this paper · explained in 7 episodes
• Compositional Generalization — 12× in this paper · explained in 4 episodes
• Actor — 11× in this paper · explained in 3 episodes
• Cognitive Gridworld — 10× in this paper
• Meta-learning — 10× in this paper · explained in 2 episodes
• Generative Model — 6× in this paper · explained in 2 episodes
• Reinforcement Learning — 6× in this paper · explained in 4 episodes
• Bayesian Inference — 5× in this paper · explained in 5 episodes
• Gradient Flow — 5× in this paper · explained in 2 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Generative Modeling — 4× in this paper · explained in 3 episodes
• Abstraction — 3× in this paper · explained in 1 episode
• Adam — 3× in this paper · explained in 2 episodes
• Adaptation — 3× in this paper · explained in 1 episode
• Computational Biology — 3× in this paper · explained in 2 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• Hallucination — 3× in this paper · explained in 3 episodes
• Temporal Correlations — 3× in this paper · explained in 2 episodes
• World Model — 3× in this paper · explained in 7 episodes
• Action Space — 2× in this paper · explained in 1 episode
• Continual Learning — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Sparsity — 2× in this paper · explained in 4 episodes
• Zero-Shot Generalization — 2× in this paper · explained in 5 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Causal Inference — 1× in this paper · explained in 4 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Curse of Dimensionality — 1× in this paper · explained in 6 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Geometric Distribution — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Multi-Agent System — 1× in this paper · explained in 5 episodes
• Partially Observable Markov Decision Process — 1× in this paper
• Partially observable Markov decision process (POMDP) — 1× in this paper · explained in 2 episodes
• Predictive Modeling — 1× in this paper · explained in 2 episodes
• Principal Component Analysis — 1× in this paper
• Principal Component Analysis (PCA) — 1× in this paper · explained in 4 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Reward Function — 1× in this paper · explained in 2 episodes

Sources

• Is Conditional Generative Modeling all you need for Decision-Making?
• V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning
• On the Measure of Intelligence
• ARC Prize 2024: Technical Report
• Active Learning with Partial Feedback
• Meta-learning of Sequential Strategies
• A Generalist Agent
• Finding Approximate POMDP solutions Through Belief Compression

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