AI RESEARCH
A Survey of Personalized Federated Foundation Models for Privacy-Preserving Recommendation
arXiv CS.LG
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ArXi:2506.11563v2 Announce Type: replace Integrating Foundation Models (FMs) into recommendation systems is an emerging and promising research direction. However, centralized paradigms face growing pressure from privacy concerns and strict regulatory requirements. Federated learning offers a viable solution that enables collaborative model refinement while keeping raw user data on local devices or organizational silos.