3 papers
cs.IR2025
Bootstrapping Conditional Retrieval for User-to-Item Recommendations
Hongtao Lin, Haoyu Chen, Jaewon Jang +1
User-to-item retrieval has been an active research area in recommendation system, and two tower models are widely adopted due to model simplicity and serving efficiency. In this wo…
cs.IR2025
Synergizing Implicit and Explicit User Interests: A Multi-Embedding Retrieval Framework at Pinterest
Zhibo Fan, Hongtao Lin, Haoyu Chen +4
Industrial recommendation systems are typically composed of multiple stages, including retrieval, ranking, and blending. The retrieval stage plays a critical role in generating a h…
cs.IR2025
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…