5 papers
Equip Pre-ranking with Target Attention by Residual Quantization
Yutong Li, Yu Zhu, Yichen Qiao +4
The pre-ranking stage in industrial recommendation systems faces a fundamental conflict between efficiency and effectiveness. While powerful models like Target Attention (TA) excel…
Beyond the Trigger: Learning Collaborative Context for Generalizable Trigger-Induced Recommendation
Chen Gao, Zixin Zhao, Lv Shao +1
In e-commerce, Trigger-Induced Recommendation (TIR), recommending items after a user clicks a trigger, is an important task. However, modern platforms rely on a continuous stream o…
Next Interest Flow: A Generative Pre-training Paradigm for Recommender Systems by Modeling All-domain Movelines
Chen Gao, Zixin Zhao, Lv Shao +1
Click-Through Rate (CTR) prediction has long been dominated by discriminative paradigms that optimize local decision boundaries within candidate-specific subspaces. However, these…
All-domain Moveline Evolution Network for Click-Through Rate Prediction
Chen Gao, Zixin Zhao, Lv Shao +1
E-commerce app users exhibit behaviors that are inherently logically consistent. A series of multi-scenario user behaviors interconnect to form the scene-level all-domain user move…
Real-time Ad retrieval via LLM-generative Commercial Intention for Sponsored Search Advertising
Tongtong Liu, Zhaohui Wang, Meiyue Qin +4
The integration of Large Language Models (LLMs) with retrieval systems has shown promising potential in retrieving documents (docs) or advertisements (ads) for a given query. Exist…