1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.IR2025
Dimension Mask Layer: Optimizing Embedding Efficiency for Scalable ID-based Models
Srijan Saket, Ikuhiro Ihara, Vaibhav Sharma +1
In modern recommendation systems and social media platforms like Meta, TikTok, and Instagram, large-scale ID-based features often require embedding tables that consume significant…
cs.SI2020★ 1 cited
Model Size Reduction Using Frequency Based Double Hashing for Recommender Systems
Caojin Zhang, Yicun Liu, Yuanpu Xie +10
Deep Neural Networks (DNNs) with sparse input features have been widely used in recommender systems in industry. These models have large memory requirements and need a huge amount…