Tag: contrastive learning

Researchers have developed a multi-granularity contrastive learning framework that automatically discovers new categories of teacher instructional behavior from classroom video, ...

A scientometric analysis of 4,269 publications charts how sentiment analysis evolved from lexicon-based polarity detection to aspect-based, multimodal, foundation-model-driven sentiment ...

Researchers have developed ALTAI, a neural network that aligns character, word, and semantic representations through cross-granularity contrastive learning to achieve ...

A new survey argues that the evolution of deep clustering is fundamentally the evolution of the prior knowledge embedded in ...

Researchers at Zhejiang University have developed a model-agnostic framework that uses large language models and the SOLO taxonomy to significantly ...

Researchers in India have built an AI framework that classifies respiratory audio with over 96 percent accuracy, offering a non-invasive ...

A new survey from the Shanghai AI Laboratory maps the explosive progress in 3D self-supervised pre-training, from contrastive learning and ...

Researchers have developed meth-SemiCancer2, a deep learning framework that combines domain adaptation and contrastive learning to correct batch effects in ...

Researchers at the Vellore Institute of Technology have built NEXUS-Rec, a five-signal neural recommender that outperforms strong baselines on MovieLens ...

A new shapelet-based soft contrastive learning framework called SCLS improves multivariate time series clustering by avoiding noisy data augmentation and ...