AI Models Flunk Engineering Simulation Test in Massive New Benchmark
A new 200,000-question benchmark from Carnegie Mellon University reveals that leading vision-language models perform at random chance when interpreting engineering ...
A new 200,000-question benchmark from Carnegie Mellon University reveals that leading vision-language models perform at random chance when interpreting engineering ...
Researchers have developed CL3AN-GNN, a graph neural network that borrows curriculum learning from education to progressively disentangle features and boost ...
Researchers in Türkiye used an explainable machine learning framework combining XGBoost and SHAP to identify age and postpartum diseases as ...
Researchers have developed a hybrid particle-filter and neural network framework that predicts lithium-ion battery remaining useful life with 99.41 percent ...
Researchers have developed a two-step machine-learning method that predicts small-molecule retention times in liquid chromatography for any experimental setup without ...
A large-scale analysis of 455,530 infection patients shows that routine blood count parameters form distinct site-associated patterns across 29 infection ...
A new simulation study compares Fourier, wavelet, and direct time-domain fitting methods for analyzing short and non-stationary NMR signals, revealing ...
A Chinese research team used CT radiomics and machine learning to distinguish harmless ground-glass lung nodules from invasive adenocarcinoma with ...
Vietnamese researchers combined field trials with machine learning to show that a precisely timed spray of the cytokinin 6-benzyladenine boosts ...
A new study shows that generative large language models can predict odor quality, capture concentration-dependent scent shifts, and outperform molecular ...
An independent evaluation in PLOS Digital Health finds that deep learning models excel at breast cancer detection from medical images ...
Researchers have developed shotgun genetic engineering, a method that screens millions of randomly assembled metabolic pathways in mammalian cells and ...
Researchers have unveiled a triple-stream deep hashing framework that compresses multi-label images into compact binary codes with higher accuracy and ...
A comparison of ten evapotranspiration partitioning methods across four Canadian moss-covered wetlands finds no consistent winner and exposes deep uncertainty ...
A new book by University of Illinois professor John Gallagher draws on interviews with more than 100 AI and machine ...
A new generative AI framework called GenFocal transforms coarse global climate model output into statistically accurate fine-scale regional weather, capturing ...
Researchers show that a selective embedding data loading strategy alternating X-ray and CT scans lets deep learning models reach competitive ...
A new survey compares marker-based, markerless and thermal imaging approaches to human pose estimation for detecting gait changes linked to ...
A new study in the Journal of Big Data shows that large language models can outperform traditional machine learning in ...
Machine learning of structural MRI and mitochondrial haplogroups can moderately predict a maternal family history of Alzheimer's disease, with precuneus ...
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