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No Attention, No Problem: Rethinking Session-based Recommendation with Pure Convolution
Session-based recommendation (SBR) predicts the next choice in a session by analyzing recent interactions. Transformer-based models are widely used because of their ability to capture long-range dependencies through self-attention mechanisms. In contrast, traditional convolutional models, although m
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