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The increasing availability and diversity of multimodal data in recommender systems offer new avenues for enhancing recommendation accuracy and user satisfaction.
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Zhong, S., Huang, Z., Li, D., Wen, W., Qin, J. & Lin, L. Mirror Gradient: Towards Robust Multimodal Recommender Systems via Exploring Flat Local Minima. Proceedings Of The ACM On Web Conference 2024
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