3 papers
cs.DB2026
TEngineDB-V: An OLAP-Native Vector Search System for Large- Workloads at Tencent
Xufei Wu, Pengcheng Zhang, Yitong Song +11
Vector search systems are essential infrastructure for modern data-driven applications. Large- analytical vector search, which retrieves -- results for analytics (…
cs.IR2025
RankMixer: Scaling Up Ranking Models in Industrial Recommenders
Jie Zhu, Zhifang Fan, Xiaoxie Zhu +18
Recent progress on large language models (LLMs) has spurred interest in scaling up recommendation systems, yet two practical obstacles remain. First, training and serving cost on i…
cs.IR2025
Large Memory Network for Recommendation
Hui Lu, Zheng Chai, Yuchao Zheng +5
Modeling user behavior sequences in recommender systems is essential for understanding user preferences over time, enabling personalized and accurate recommendations for improving…