The ability to predict brain activity from words before they occur can be explained by information shared between neighbouring words, without requiring next-word prediction by the brain.

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 ...

The scaling of inference-time compute has become a primary driver for Large Language Model (LLM) performance, shifting architectural focus toward inference efficiency alongside model quality. While ...