Diffusion Model Turns Sparse User Histories into Better Cold-Start Recommendations
A new diffusion-based framework extracts transferable preference patterns from historical user data to improve recommendations for users with almost no ...
A new diffusion-based framework extracts transferable preference patterns from historical user data to improve recommendations for users with almost no ...
A new recommender model called COMPASS learns a user-specific allocation over spectral bands instead of a fixed truncation rank, improving ...
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