141 citations · 279 across the 13 of their papers we have counts for
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TransAct: Transformer-based Realtime User Action Model for Recommendation at Pinterest
Xue Xia, Pong Eksombatchai, Nikil Pancha +7
Sequential models that encode user activity for next action prediction have become a popular design choice for building web-scale personalized recommendation systems. Traditional m…
Rethinking Personalized Ranking at Pinterest: An End-to-End Approach
Jiajing Xu, Andrew Zhai, Charles Rosenberg
In this work, we present our journey to revolutionize the personalized recommendation engine through end-to-end learning from raw user actions. We encode user's long-term interest…
ItemSage: Learning Product Embeddings for Shopping Recommendations at Pinterest
Paul Baltescu, Haoyu Chen, Nikil Pancha +3
Learned embeddings for products are an important building block for web-scale e-commerce recommendation systems. At Pinterest, we build a single set of product embeddings called It…