Multi-modal video data-pipelines for machine learning with minimal human supervision 事件

Multi-modal video data-pipelines for machine learning with minimal human supervision arXiv:2510.14862v2 Announce Type: replace Abstract: The real-world is inherently multi-modal at its core. Our tools observe and take snapshots of it, in digital form, such as videos or sounds, however much of it is lost. Similarly for actions and information passing between humans, languages are used as a written form of communication. Traditionally, Machine Learning models have been unimodal (i.e. rgb -> seman