Turkish researchers show that behavior-preserving code refactoring used to synthesize training data, combined with GraphCodeBERT embeddings, markedly improves deep learning...

Researchers have introduced AI Flow, a framework combining device-edge-cloud collaboration, familial models, and networked intelligence emergence to make powerful AI...

Researchers have developed a deterministic duel-based imputation framework that selects missing-data replacements by directly testing candidates against forecasting performance, cutting...

A comprehensive review shows that artificial intelligence, from hyperspectral sensing and climate-driven forecasting to autonomous drones and ground robots, is...

Researchers developed optimized hybrid XGBoost models that accurately predict blast-induced flyrock distances at Iran's Sungun Copper Mine while identifying powder...

A new dual-branch deep learning framework combining GAN-based super-resolution and transformer spectral modeling achieves over 99 percent accuracy classifying hyperspectral...

Researchers have developed TRACE, a self-supervised framework that teaches video AI models to reason about interventions and counterfactuals rather than...

University of South Carolina researcher Fanghui Shi has received a five-year, $2.2 million NIH Director's New Innovator Award to use...

A new study shows that embeddings from a pretrained chemical language model nearly match classical QSAR methods in predicting which...

A self-supervised language model called NucleicBERT offers researchers a new computational lens on the vast and poorly charted space of...