A2G-DiffRec applies adaptive autoguidance in diffusion recommenders, learning to balance main and weak model outputs via fairness-aware regularization to improve item exposure fairness with only marginal accuracy loss.
Synthetic mobility feature generation for mental health prediction using diffusion models
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Adaptive Autoguidance for Item-Side Fairness in Diffusion Recommender Systems
A2G-DiffRec applies adaptive autoguidance in diffusion recommenders, learning to balance main and weak model outputs via fairness-aware regularization to improve item exposure fairness with only marginal accuracy loss.
- DAD4TS: Data-Augmentation-Oriented Diffusion Model for Time-Series Forecasting with Small-Scale Data