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.

LLMs are quietly reshaping data journalism workflows at The Hindu, helping reporters process vast document sets, write ...

Microsoft's Bing team has open-sourced Harrier, an embedding model family that tops the multilingual MTEB v2 benchmark under an MIT license.

Abstract: Accurate segmentation of pulmonary infection regions is critical for diagnosing respiratory diseases such as COVID-19 and pneumonia. Although recent deep learning approaches have achieved ...

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 ...

Deep learning models for decoding intracortical neural activity during attempted speech into text. This repository contains our team's implementation for the COMP 433 Fall 2025 course project, ...

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

Multimodal AI pipelines typically require separate models to handle text, images, video, and audio, each adding transcription overhead, latency, and cost before any search query can even run. Google’s ...