GALA: Generative Aligned Learning for Adaptive Multimodal Representation in the Taobao Shangou Recommender System

arXiv:2607. 29213v1 Announce Type: cross Abstract: Modern recommender systems in food delivery increasingly leverage multimodal signals, including images, text, and user interaction histories, to enhance user experience, yet effective fusion of these heterogeneous modalities remains challenging, hindering both the joint modeling of multimodal signals and adaptation to evolving user intent.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

• rag
• reinforcement-learning
• fine-tuning
• multimodal
• benchmarks
• safety