Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond

arXiv:2403.10667v1 Announce Type: cross
Abstract: Developing a universal model that can effectively harness heterogeneous resources and respond to a wide range of personalized needs has been a longstanding community aspiration. Our daily choices, especially in domains like fashion and retail, are substantially shaped by multi-modal data, such as pictures and textual descriptions. These modalities not only offer intuitive guidance but also cater to personalized user preferences. However, the predominant personalization approaches mainly focus on the ID or text-based recommendation problem, …

abstract arxiv beyond community cs.ai cs.cl cs.ir cs.mm daily data domains fashion generative harness language language models modal multi-modal personalization personalized recommendation resources retail type universal universal model vision vision-language models