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

Abstract: Recently, weakly supervised methods for scene text spotter are increasingly popular with researchers due to their potential to significantly reduce dataset annotation efforts. The latest ...

Abstract: The application of automated guided vehicle (AGV) greatly improves the production efficiency of workshop. However, machine flexibility and limited logistics equipment increase the complexity ...

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 ...