2 papers
cs.IR2026
GAP-Net: Calibrating User Intent via Gated Adaptive Progressive Learning for CTR Prediction
Shenqiang Ke, Jianxiong Wei, Qingsong Hua
Sequential user behavior modeling is pivotal for Click-Through Rate (CTR) prediction yet is hindered by three intrinsic bottlenecks: (1) the "Attention Sink" phenomenon, where stan…
cs.IR2024
Treatment Effect Estimation for User Interest Exploration on Recommender Systems
Jiaju Chen, Wenjie Wang, Chongming Gao +3
Recommender systems learn personalized user preferences from user feedback like clicks. However, user feedback is usually biased towards partially observed interests, leaving many…