1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.IR2026
IAT: Instance-As-Token Compression for Historical User Sequence Modeling in Industrial Recommender Systems
Xinchun Li, Ning Zhang, Qianqian Yang +11
Although sophisticated sequence modeling paradigms have achieved remarkable success in recommender systems, the information capacity of hand-crafted sequential features constrains…
cs.LG2024★ 1 cited
Towards Few-Shot Learning in the Open World: A Review and Beyond
Hui Xue, Yuexuan An, Yongchun Qin +5
Human intelligence is characterized by our ability to absorb and apply knowledge from the world around us, especially in rapidly acquiring new concepts from minimal examples, under…