4 papers
Beyond KAN: Introducing KarSein for Adaptive High-Order Feature Interaction Modeling in CTR Prediction
Yunxiao Shi, Wujiang Xu, Haimin Zhang +2
Modeling high-order feature interactions is crucial for click-through rate (CTR) prediction, yet traditional approaches typically predefine a maximum interaction order and exhausti…
MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models
Yunxiao Shi, Shuo Yang, Haimin Zhang +4
Neural Collaborative Filtering models are widely used in recommender systems but are typically trained under static settings, assuming fixed data distributions. This limits their a…
PersonaX: A Recommendation Agent Oriented User Modeling Framework for Long Behavior Sequence
Yunxiao Shi, Wujiang Xu, Zeqi Zhang +3
User profile embedded in the prompt template of personalized recommendation agents play a crucial role in shaping their decision-making process. High-quality user profiles are esse…
Enhancing News Recommendation with Hierarchical LLM Prompting
Hai-Dang Kieu, Delvin Ce Zhang, Minh Duc Nguyen +3
Personalized news recommendation systems often struggle to effectively capture the complexity of user preferences, as they rely heavily on shallow representations, such as article…