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Found 2 papers, 2 papers with code
InternVideo2: Scaling Video Foundation Models for Multimodal Video Understanding
We introduce InternVideo2, a new video foundation model (ViFM) that achieves the state-of-the-art performance in action recognition, video-text tasks, and video-centric dialogue.
Ranked #1 on
Zero-Shot Video Question Answer
on MVBench
Collaboration and Transition: Distilling Item Transitions into Multi-Query Self-Attention for Sequential Recommendation
Second, we develop a transition-aware embedding distillation module that distills global item-to-item transition patterns into item embeddings, which enables the model to memorize and leverage transitional signals and serves as a calibrator for collaborative signals.
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