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

Numbers are the language of science—yet in research articles, they are often buried within the text and difficult to analyze.

In an era defined by rapid AI adoption, securing software has become increasingly complex. As organizations integrate AI-driven features into ...

Benchmarking four compact LLMs on a Raspberry Pi 500+ shows that smaller models such as TinyLlama are far more practical for local edge workloads, while reasoning-focused models trade latency for ...