32 citations · 68 across the 7 of their papers we have counts for
7 papers
OpenAI GPT-5 System Card
Aaditya Singh, Adam Fry, Adam Perelman +483
This is the system card published alongside the OpenAI GPT-5 launch, August 2025. GPT-5 is a unified system with a smart and fast model that answers most questions, a deeper reason…
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…
OmniSearchSage: Multi-Task Multi-Entity Embeddings for Pinterest Search
Prabhat Agarwal, Minhazul Islam Sk, Nikil Pancha +3
In this paper, we present OmniSearchSage, a versatile and scalable system for understanding search queries, pins, and products for Pinterest search. We jointly learn a unified quer…
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…
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…
MultiBiSage: A Web-Scale Recommendation System Using Multiple Bipartite Graphs at Pinterest
Saket Gurukar, Nikil Pancha, Andrew Zhai +5
Graph Convolutional Networks (GCN) can efficiently integrate graph structure and node features to learn high-quality node embeddings. These embeddings can then be used for several…
PinnerFormer: Sequence Modeling for User Representation at Pinterest
Nikil Pancha, Andrew Zhai, Jure Leskovec +1
Sequential models have become increasingly popular in powering personalized recommendation systems over the past several years. These approaches traditionally model a user's action…