VidPrism: Heterogeneous Mixture of Experts for Image-to-Video Transfer 事件

VidPrism: Heterogeneous Mixture of Experts for Image-to-Video Transfer arXiv:2605.28229v1 Announce Type: new Abstract: With the rapid development of pre-training technologies, adapting large-scale Vision-Language Models (VLMs) for video understanding \emph{\ie} image-to-video transfer learning has become a dominant paradigm. To achieve superior performance, it raises as an effective strategy among recent advances to employ Mixture-of-Experts (MoE) to enhance VLMs' temporal modeling capabilities