Leveraging Generative Models to Enhance Modern Recommender Systems

Generative models, including auto-encoding, auto-regressive, adversarial, and diffusion models, have significantly enhanced the capabilities of modern recommender systems by enabling them to model and sample from complex data distributions beyond just user-item interactions.