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Predictive Self-Supervised Learning Provably Identifies Stochastic Signals under Nuisance2h◆Pixel-Level Transformers in Remote Sensing: A Canopy Height Case Study2h◆Explore, Execute, Evolve: A Skill Acquisition and Reuse Loop for Embodied Agents2h◆Boosting Adversarial Robustness and Generalization with Dictionary Structure2h◆Making Duplicate Reimbursement Unrepresentable: A Verified Ethereum E-Invoice System for Humans and AI Agents2h◆HandAnthro: Automated Hand Anthropometry from a Single Image2h◆AgentBug-Smith: Automatically Reproducing Real-World Harness Bugs in Agentic Systems2h◆A Dominant Supplier Slows Recursive Drift More Than It Steers It2h◆COMiT: Learning Structured Visual Tokens through Sequential Communication2h◆PAC-CF: Calibrating Irreversible Frontier Pruning in LLM-Guided Search2h◆RobotValues: Evaluating Household Robots When Human Values Conflict2h◆TacForcing: Streaming Action Generation with Execution-Time Tactile Feedback2h◆Learning Spectrally Optimised Mesh-Free Discretisations2h◆Question-Specific Knowledge Graphs for Efficient Visual Reasoning2h◆Dropout Universality: Scaling Laws and Optimal Scheduling at the Edge-of-Chaos2h◆Local Search with Correlated Randomness2h◆When Can Prefixes Compile LoRA? Exact Resource-Capped Tests for Frozen Attention2h◆How Can Recommendation Feedback Evolve Agent Memory?2h◆Sage: Formalization with Semantic Correction2h◆Alignment Forecasting: Predicting Misalignment From Training Data2h◆Predictive Self-Supervised Learning Provably Identifies Stochastic Signals under Nuisance2h◆Pixel-Level Transformers in Remote Sensing: A Canopy Height Case Study2h◆Explore, Execute, Evolve: A Skill Acquisition and Reuse Loop for Embodied Agents2h◆Boosting Adversarial Robustness and Generalization with Dictionary Structure2h◆Making Duplicate Reimbursement Unrepresentable: A Verified Ethereum E-Invoice System for Humans and AI Agents2h◆HandAnthro: Automated Hand Anthropometry from a Single Image2h◆AgentBug-Smith: Automatically Reproducing Real-World Harness Bugs in Agentic Systems2h◆A Dominant Supplier Slows Recursive Drift More Than It Steers It2h◆COMiT: Learning Structured Visual Tokens through Sequential Communication2h◆PAC-CF: Calibrating Irreversible Frontier Pruning in LLM-Guided Search2h◆RobotValues: Evaluating Household Robots When Human Values Conflict2h◆TacForcing: Streaming Action Generation with Execution-Time Tactile Feedback2h◆Learning Spectrally Optimised Mesh-Free Discretisations2h◆Question-Specific Knowledge Graphs for Efficient Visual Reasoning2h◆Dropout Universality: Scaling Laws and Optimal Scheduling at the Edge-of-Chaos2h◆Local Search with Correlated Randomness2h◆When Can Prefixes Compile LoRA? Exact Resource-Capped Tests for Frozen Attention2h◆How Can Recommendation Feedback Evolve Agent Memory?2h◆Sage: Formalization with Semantic Correction2h◆Alignment Forecasting: Predicting Misalignment From Training Data2h◆
News/Predictive Self-Supervised Learning Provably Identifies Stochastic Signals under Nuisance
arxiv
PublishedSeptember 30, 2026 at 4:00 AM
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Predictive Self-Supervised Learning Provably Identifies Stochastic Signals under Nuisance

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arXiv:2609.37789v1 Announce Type: cross Abstract: Self-supervised learning (SSL) by predicting in latent space, without generating the input data itself, learns highly abstract, useful representations. Intuitively, this success is often attributed to its ability to discard nuisance information that

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