4 citations · 5 across the 5 of their papers we have counts for
3 papers · 1 filter
PinFM: Foundation Model for User Activity Sequences at a Billion-scale Visual Discovery Platform
Xiangyi Chen, Kousik Rajesh, Matthew Lawhon +9
User activity sequences have emerged as one of the most important signals in recommender systems. We present a foundational model, PinFM, for understanding user activity sequences…
TransAct V2: Lifelong User Action Sequence Modeling on Pinterest Recommendation
Xue Xia, Saurabh Vishwas Joshi, Kousik Rajesh +6
Modeling user action sequences has become a popular focus in industrial recommendation system research, particularly for Click-Through Rate (CTR) prediction tasks. However, industr…
OmniSage: Large Scale, Multi-Entity Heterogeneous Graph Representation Learning
Anirudhan Badrinath, Alex Yang, Kousik Rajesh +5
Representation learning, a task of learning latent vectors to represent entities, is a key task in improving search and recommender systems in web applications. Various representat…