3 papers
cs.IR2026
Light-FMP: Lightweight Feature and Model Pruning for Enhanced Deep Recommender Systems
Nghia Bui, Yue Ning, Lijing Wang
Deep recommender systems (DRS) often face challenges in balancing computational efficiency and model accuracy, especially when handling high-dimensional input features. Existing me…
cs.LG2026
Lightweight Fairness for LLM-Based Recommendations via Kernelized Projection and Gated Adapters
Nan Cui, Wendy Hui Wang, Yue Ning
Large Language Models (LLMs) have introduced new capabilities to recommender systems, enabling dynamic, context-aware, and conversational recommendations. However, LLM-based recomm…
cs.CL2024
Large Language Models as Interpolated and Extrapolated Event Predictors
Libo Zhang, Yue Ning
Salient facts of sociopolitical events are distilled into quadruples following a format of subject, relation, object, and timestamp. Machine learning methods, such as graph neural…