3 papers
cs.IR2026
An Industrial-Scale Sequential Recommender for LinkedIn Feed Ranking
Lars Hertel, Gaurav Srivastava, Syed Ali Naqvi +21
LinkedIn Feed enables professionals worldwide to discover relevant content, build connections, and share knowledge at scale. We present Feed Sequential Recommender (Feed SR), a tra…
cs.LG2025
From Features to Transformers: Redefining Ranking for Scalable Impact
Fedor Borisyuk, Lars Hertel, Ganesh Parameswaran +14
We present LiGR, a large-scale ranking framework developed at LinkedIn that brings state-of-the-art transformer-based modeling architectures into production. We introduce a modifie…
cs.IR2024
LiMAML: Personalization of Deep Recommender Models via Meta Learning
Ruofan Wang, Prakruthi Prabhakar, Gaurav Srivastava +10
In the realm of recommender systems, the ubiquitous adoption of deep neural networks has emerged as a dominant paradigm for modeling diverse business objectives. As user bases cont…