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Europe needs 65 CO2 carriers and 33 ports by 2050 to meet carbon storage goals, Xodus report says LLMs Struggle with Multi-Step Logic: New Framework DREAM Boosts Theorem Proving Performance The Missing Knowledge Layer in Cognitive Architectures for AI Agents RealityBridge: New AI Framework Edits 3D Driving Simulations to Close the Sim-to-Real Gap Reinforcement Learning with Chain-of-Thought Supervision Boosts Hateful Meme Detection Accuracy by Over 2% ATOM-Bench: New Benchmark Evaluates Atomic Skills and Compositional Generalization in Robotic Manipulation Policies FusionRS Dataset Advances Dual-Modal Vision-Language AI for Remote Sensing CAP Achieves 87.6% Improvement in Respiratory Rate Prediction via Patient-Level PPG Learning LLM-WikiRace Benchmark Reveals Frontier AI Models Still Struggle with Planning Over Knowledge Graphs New Research Demystifies Variance in Circuit Discovery of Large Language Models Europe needs 65 CO2 carriers and 33 ports by 2050 to meet carbon storage goals, Xodus report says LLMs Struggle with Multi-Step Logic: New Framework DREAM Boosts Theorem Proving Performance The Missing Knowledge Layer in Cognitive Architectures for AI Agents RealityBridge: New AI Framework Edits 3D Driving Simulations to Close the Sim-to-Real Gap Reinforcement Learning with Chain-of-Thought Supervision Boosts Hateful Meme Detection Accuracy by Over 2% ATOM-Bench: New Benchmark Evaluates Atomic Skills and Compositional Generalization in Robotic Manipulation Policies FusionRS Dataset Advances Dual-Modal Vision-Language AI for Remote Sensing CAP Achieves 87.6% Improvement in Respiratory Rate Prediction via Patient-Level PPG Learning LLM-WikiRace Benchmark Reveals Frontier AI Models Still Struggle with Planning Over Knowledge Graphs New Research Demystifies Variance in Circuit Discovery of Large Language Models

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physics-informed

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Phys-JEPA Model Promises More Accurate Multivariate Time-Series Forecasting with Physics-Informed Latent States

Artificial Intelligence #physics-informed#latent world models

Phys-JEPA Model Promises More Accurate Multivariate Time-Series Forecasting with Physics-Informed Latent States

Phys-JEPA is a new architecture that imposes physical consistency on latent states rather than only on outputs, improving multivariate time-series forecasting. On standard benchmarks, it reduces mean squared error across multiple horizons, suggesting a promising direction for interpretable temporal world models.

Jun 16, 2026 1 source

Geometry-Aware Neural Operator Cuts Simulation Time for Plate Structures from Hours to Milliseconds

Artificial Intelligence #machine learning#physics-informed

Geometry-Aware Neural Operator Cuts Simulation Time for Plate Structures from Hours to Milliseconds

Researchers propose MR-GVNO, a geometry-aware variational neural operator for Mindlin-Reissner plate problems. The model uses boundary point clouds and cross-attention to predict responses on irregular domains, achieving millisecond-level inference without labeled training data.

Jun 16, 2026 1 source