AI news

AAAI 2026 Oral | UTS and PolyU Break the “One-Size-Fits-All” Mold: How Federated Recommendation Achieves Personalized Image-Text Fusion

AI news

AAAI 2026 Oral | UTS and PolyU Break the “One-Size-Fits-All” Mold: How Federated Recommendation Achieves Personalized Image-Text Fusion

Balancing Privacy & Personalization in Multimodal Recommendation Systems In today’s move toward multimodal recommendation systems, the challenge is how to balance data privacy with personalized image–text understanding. A research team led by Prof. Guodong Long (University of Technology Sydney), in collaboration with Prof. Qiang Yang and Prof. Chengqi