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cs.IR2025
Scaling Laws for Online Advertisement Retrieval
Yunli Wang, Zhen Zhang, Zixuan Yang +9
The scaling law is a notable property of neural network models and has significantly propelled the development of large language models. Scaling laws hold great promise in guiding…
cs.IR2025
Learning Cascade Ranking as One Network
Yunli Wang, Zhen Zhang, Zhiqiang Wang +6
Cascade Ranking is a prevalent architecture in large-scale top-k selection systems like recommendation and advertising platforms. Traditional training methods focus on single-stage…
cs.IR2025
Hierarchical Tree Search-based User Lifelong Behavior Modeling on Large Language Model
Yu Xia, Rui Zhong, Hao Gu +4
Large Language Models (LLMs) have garnered significant attention in Recommendation Systems (RS) due to their extensive world knowledge and robust reasoning capabilities. However, a…