Tag: transformers

A systematic review of 90 peer-reviewed studies charts how artificial intelligence is reshaping litigation while exposing persistent challenges in explainability, ...

Researchers have introduced a Riemannian manifold-based loss function that pushes multimodal Transformer models to state-of-the-art accuracy in human activity recognition ...

A new systematic review in Neural Computing and Applications maps the capabilities of modern large language models into six categories ...

A new survey maps how large language models and vision-language models are enabling gloss-free sign language translation to break communication ...

Researchers in China have developed a neighbor-constrained attention framework that improves how artificial intelligence classifies gigapixel whole-slide pathology images by ...

A multimodal AI model called ERF-BA-TFD+ detects and localizes audio-visual deepfakes by cross-reconstructing audio and video features and reasoning over ...

A new systematic study shows that low-rank adaptation can match or approach full fine-tuning of transformer models across four sentiment ...

A systematic review of 93 studies reveals eight attack types and nine defence types across six categories of unsupervised machine ...

A sweeping new survey of 57 studies finds that machine learning and deep learning models report accuracy as high as ...

Researchers at the Norwegian University of Science and Technology have developed two new explainability methods that integrate transformer attention weights ...