3 papers
cs.IR2026
Isotonic Layer: A Unified Framework for Recommendation Calibration and Debiasing
Hailing Cheng, Yafang Yang, Hemeng Tao +1
Model calibration and debiasing are fundamental yet operationally expensive challenges in large-scale recommendation systems. Existing approaches treat them as separate problems re…
cs.LG2025
LinkedIn Post Embeddings: Industrial Scale Embedding Generation and Usage across LinkedIn
Sudarshan Srinivasa Ramanujam, Akanksha Bindal, Yu Jiang +8
A post embedding (representation of text in embedding space that effectively captures semantic meaning) is a foundational component of LinkedIn that is consumed by product surfaces…
cs.LG2024
LiRank: Industrial Large Scale Ranking Models at LinkedIn
Fedor Borisyuk, Mingzhou Zhou, Qingquan Song +31
We present LiRank, a large-scale ranking framework at LinkedIn that brings to production state-of-the-art modeling architectures and optimization methods. We unveil several modelin…