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Controlling Diversity at Inference: Guiding Diffusion Recommender Models with Targeted Category Preferences
Diversity control is an important task to alleviate bias amplification and filter bubble
problems. The desired degree of diversity may fluctuate based on users' daily moods or …
problems. The desired degree of diversity may fluctuate based on users' daily moods or …
CF-KAN: Kolmogorov-Arnold network-based collaborative filtering to mitigate catastrophic forgetting in recommender systems
Collaborative filtering (CF) remains essential in recommender systems, leveraging user--
item interactions to provide personalized recommendations. Meanwhile, a number of CF …
item interactions to provide personalized recommendations. Meanwhile, a number of CF …