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Found 3 papers, 2 papers with code
Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey
The recent advancements in pretrained multimodal models offer new opportunities and challenges in developing content-aware recommender systems.
ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems
Secondly, the existing literature's lack of detailed analysis on selection attributes, based on large-scale datasets and a thorough comparison among selection techniques and DRS backbones, restricts the generalizability of findings and impedes deployment on DRS.
Diffusion Augmentation for Sequential Recommendation
However, sequential recommendation often faces the problem of data sparsity, which widely exists in recommender systems.
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