Dynamic Evidence Calibration and Interest Evolution for Multimodal Video Recommendation
Multimodal video recommendation in feed-based systems requires capturing how user interest evolves within and across videos, yet existing fine-grained methods suffer from three key limitations: (1) they treat preference matching as a static, context-free similarity computation over user history; (2) they assume user at...