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Found 4 papers, 1 papers with code
Repeated Padding as Data Augmentation for Sequential Recommendation
Specifically, we use the original interaction sequences as the padding content and fill it to the padding positions during model training.
ID Embedding as Subtle Features of Content and Structure for Multimodal Recommendation
In this paper, we revisit the value of ID embeddings for multimodal recommendation and conduct a thorough study regarding its semantics, which we recognize as subtle features of content and structures.
Video and Audio are Images: A Cross-Modal Mixer for Original Data on Video-Audio Retrieval
Cross-modal retrieval has become popular in recent years, particularly with the rise of multimedia.
Uniform Sequence Better: Time Interval Aware Data Augmentation for Sequential Recommendation
However, we observe that the time interval in a sequence may vary significantly different, and thus result in the ineffectiveness of user modeling due to the issue of \emph{preference drift}.
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