In this episode, we delve into the transformative impact of Generative Models on modern Recommender Systems (RS), as detailed in the comprehensive survey titled "A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)". This multidisciplinary study explores how traditional RS, which primarily relied on user-item rating histories, are evolving through the integration of advanced generative techniques.

Key Discussion Points:

• Interaction-Driven Generative Models: We examine how models like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) are utilized to capture complex user-item interactions, enabling the generation of personalized recommendations beyond historical data.
• Large Language Models ( ...