145 citations · 146 across the 4 of their papers we have counts for
4 papers
Generative Long-term User Interest Modeling for Click-Through Rate Prediction
Jiangli Shao, Kaifu Zheng, Hao Fang +5
Modeling long-term user interests with massive historical user behaviors enhances click-through rate (CTR) prediction performance in advertising and recommendation systems. Typical…
An Efficient Embedding Based Ad Retrieval with GPU-Powered Feature Interaction
Yifan Lei, Jiahua Luo, Tingyu Jiang +7
In large-scale advertising recommendation systems, retrieval serves as a critical component, aiming to efficiently select a subset of candidate ads relevant to user behaviors from…
Multiple Key-value Strategy in Recommendation Systems Incorporating Large Language Model
Dui Wang, Xiangyu Hou, Xiaohui Yang +3
Recommendation system (RS) plays significant roles in matching users information needs for Internet applications, and it usually utilizes the vanilla neural network as the backbone…
Multiplex Behavioral Relation Learning for Recommendation via Memory Augmented Transformer Network
Lianghao Xia, Chao Huang, Yong Xu +3
Capturing users' precise preferences is of great importance in various recommender systems (eg., e-commerce platforms), which is the basis of how to present personalized interestin…