Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).
Foundation model-powered dual-module system establishes a new performance benchmark for AI-driven peptide drug ...
This study presents KEPT, an AI system that helps self-driving cars predict their own short-term path more safely by combining video understanding ...
This study presents KEPT, an AI system that helps self-driving cars predict their own short-term path more safely by ...
Abstract: Sleep staging is critical to assess sleep quality and diagnose sleep disorders. Traditional sleep staging methods usually ignore the interactions between different-scale features and lack ...
To build a self-supervised magnetic resonance imaging (MRI) foundation model from routine clinical scans and to test whether it can support key glioma-related applications, including post-therapy ...
Google announced a major update to voice search that uses AI to make it faster and more accurate, calling it a new era. Google announced an update to its voice search, which changes how voice search ...
Why was a new multilingual encoder needed? XLM-RoBERTa (XLM-R) has dominated multilingual NLP for more than 5 years, an unusually long reign in AI research. While encoder-only models like BERT and ...
This is the official repository for the paper "Prot2Text-V2: Protein Function Prediction with Multimodal Contrastive Alignment" by Xiao Fei, Michail Chatzianastasis, Sarah Almeida Carneiro, Hadi ...
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