Ni, Yabo

1. Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks
   2018/05/28 by Yabo Ni, Dan Ou, Ni, Yabo +11 · 6 citations
   Computer Science · #Expert finding and Q&A systems #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Recommender Systems and Techniques #Topic Modeling
2. OnePiece: Bringing Context Engineering and Reasoning to Industrial Cascade Ranking System
   2025/09/22 by Sunhao Dai, Dai, Sunhao, Jiakai Tang +28 · 9 citations
   Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Semantic Web and Ontologies #Service-Oriented Architecture and Web Services
3. Clustered Embedding Learning for Recommender Systems
   2023/02/03 by Yizhou Chen, Guangda Huzhang, Chen, Yizhou +17 · 2 citations
   Computer Science · Social Sciences · #Advanced Graph Neural Networks #Artificial Intelligence (cs.AI) #Digital Marketing and Social Media #FOS: Computer and information sciences #Machine Learning (cs.LG) #Recommender Systems and Techniques
4. Residual Multi-Task Learner for Applied Ranking
   2024/10/30 by C. D. Fu, Kun Wang, Fu, Cong +13 · 3 citations
   Computer Science · #FOS: Computer and information sciences #Face and Expression Recognition #Information Retrieval (cs.IR) #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and Data Classification
5. Maximum Inner Product is Query-Scaled Nearest Neighbor
   2025/03/10 by Chen, Tingyang, Fu, Cong, Wang, Kun +5 · 2 citations
   #Databases (cs.DB) #FOS: Computer and information sciences
6. Stitching Inner Product and Euclidean Metrics for Topology-aware Maximum Inner Product Search
   2025/04/21 by Chen, Tingyang, Fu, Cong, Ke, Xiangyu +3 · 3 citations
   #Databases (cs.DB) #FOS: Computer and information sciences #Information Retrieval (cs.IR)