3 papers
cs.IR2026
UniPinRec: Unifying Generative Retrieval and Ranking at Pinterest Scale
Hanyu Li, Yi-Ping Hsu, Aditya Mantha +17
Modern recommendation systems predominantly train retrieval and ranking as separate models despite both increasingly relying on large transformers encoding the same user behavior d…
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…