Gradient-based representations paired with distribution-matching enable efficient curation of small data subsets that improve performance and training efficiency for continually adapting generative recommenders while maintaining robustness to distributional drift.
Continuous learning over time.Continuous learning research addresses when and how models should be updated as data distributions shift
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Efficient Dataset Selection for Continual Adaptation of Generative Recommenders
Gradient-based representations paired with distribution-matching enable efficient curation of small data subsets that improve performance and training efficiency for continually adapting generative recommenders while maintaining robustness to distributional drift.