14 citations · 26 across the 7 of their papers we have counts for
7 papers
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…
InteractRank: Personalized Web-Scale Search Pre-Ranking with Cross Interaction Features
Sujay Khandagale, Bhawna Juneja, Prabhat Agarwal +3
Modern search systems use a multi-stage architecture to deliver personalized results efficiently. Key stages include retrieval, pre-ranking, full ranking, and blending, which refin…
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…
PinRec: Unified Generative Retrieval for Pinterest Recommender Systems
Edoardo Botta, Jaewon Yang, Yi-Ping Hsu +6
Generative retrieval methods employ sequential modeling techniques, like transformers, to generate candidate items for recommender systems. These methods have demonstrated promisin…
Unified Preference Optimization: Language Model Alignment Beyond the Preference Frontier
Anirudhan Badrinath, Prabhat Agarwal, Jiajing Xu
For aligning large language models (LLMs), prior work has leveraged reinforcement learning via human feedback (RLHF) or variations of direct preference optimization (DPO). While DP…
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…
Modeling User Behavior With Interaction Networks for Spam Detection
Prabhat Agarwal, Manisha Srivastava, Vishwakarma Singh +1
Spam is a serious problem plaguing web-scale digital platforms which facilitate user content creation and distribution. It compromises platform's integrity, performance of services…