Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).

Abstract: Infrared small target detection (ISTD) faces significant challenges in effectively utilizing shallow and deep features while mitigating spatial detail degradation during sampling. To address ...

James Marsden isn’t the type of guy to “hard launch” a relationship. The Paradise actor waited two years before even making his first red carpet appearance with his current girlfriend, Dutch model ...

Hallucination is one of the most critical obstacles to reliably deploying Large Vision-Language Models (LVLMs): the model produces fluent, confident text that is factually inconsistent with what is ...

Neuroscience has long been a field of divide and conquer. Researchers typically map specific cognitive functions to isolated brain regions—like motion to area V5 or faces to the fusiform gyrus—using ...

Summary: Meta’s Fundamental AI Research team has unveiled TRIBE, a groundbreaking foundation model designed to predict how the human brain processes visual and auditory stimuli. Trained on massive ...

Abstract: In deep learning-based dehazing strategies, attention mechanisms are widely used to refine feature representations and improve overall performance. However, conventional contextual attention ...