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cs.IR2026
Towards a Densing Law for User Representation Learning at Billion-Scale Capacity
Bin Dou, Junru Zhang, Zhaoyi Yuan +6
User representation learning in real-world industrial scenarios is commonly scaled by increasing user amount, behavioral sequence length and model size. However, existing methods f…
cs.IR2024
Multi-Grained Preference Enhanced Transformer for Multi-Behavior Sequential Recommendation
Chuan He, Yongchao Liu, Qiang Li +5
Sequential recommendation (SR) aims to predict the next purchasing item according to users' dynamic preference learned from their historical user-item interactions. To improve the…