20 citations · 41 across the 5 of their papers we have counts for
5 papers
MTGR: Industrial-Scale Generative Recommendation Framework in Meituan
Ruidong Han, Bin Yin, Shangyu Chen +12
Scaling law has been extensively validated in many domains such as natural language processing and computer vision. In the recommendation system, recent work has adopted generative…
MTGenRec: An Efficient Distributed Training System for Generative Recommendation Models in Meituan
Yuxiang Wang, Chi Ma, Xiao Yan +15
Recommendation is crucial for both user experience and company revenue in Meituan as a leading lifestyle company, and generative recommendation models (GRMs) are shown to produce q…
Enhancing CTR Prediction through Sequential Recommendation Pre-training: Introducing the SRP4CTR Framework
Ruidong Han, Qianzhong Li, He Jiang +4
Understanding user interests is crucial for Click-Through Rate (CTR) prediction tasks. In sequential recommendation, pre-training from user historical behaviors through self-superv…
SoK: Applying Machine Learning in Security - A Survey
Heju Jiang, Jasvir Nagra, Parvez Ahammad
The idea of applying machine learning(ML) to solve problems in security domains is almost 3 decades old. As information and communications grow more ubiquitous and more data become…
A recommender system for efficient discovery of new anomalies in large-scale access logs
Heju Jiang, Scott Algatt, Parvez Ahammad
We present a novel, non-standard recommender system for large-scale security policy management(SPM). Our system Helios discovers and recommends unknown and unseen anomalies in larg…