4 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.IR2026
Unleashing the Potential of Sparse Attention on Long-term Behaviors for CTR Prediction
Weijiang Lai, Beihong Jin, Di Zhang +5
In recent years, the success of large language models (LLMs) has driven the exploration of scaling laws in recommender systems. However, models that demonstrate scaling laws are ac…
cs.IR2025★ 4 cited
Exploring Scaling Laws of CTR Model for Online Performance Improvement
Weijiang Lai, Beihong Jin, Jiongyan Zhang +5
CTR models play a vital role in improving user experience and boosting business revenue in many online personalized services. However, current CTR models generally encounter bottle…