Brief

Researchers have developed a Learnable Frame Selector (LFS) to improve video captioning by intelligently selecting relevant frames. Unlike uniform sampling, LFS balances temporal diversity and event relevance, using feedback from large language models to optimize caption quality. This method has shown improvements on existing benchmarks and a new dataset, ICH-CC, and also enhances video question answering performance. AI

Hugging Face is transitioning its model and dataset hosting platform, the Hugging Face Hub, away from Git Large File Storage (LFS) to Xet, a new version control system designed for large files. This move aims to improve performance and scalability for managing the vast amounts of data associated with AI models. The migration process is expected to be gradual, with users being notified and guided through the transition. AI