Building robust deep recommender systems: Utilizing a weighted adversarial noise propagation framework with robust fine-tuning modules

Published: 01 Jan 2025, Last Modified: 19 May 2025Knowl. Based Syst. 2025EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Highlights•We propose RAWP-FT to boost model robustness while maintaining generalization.•RAWP-FT uses weight perturbations and robust fine-tuning to improve model robustness.•RAWP-FT tested on MLP enhances model robustness under adversarial conditions.
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