2 papers
cs.IR2026
GRAB: An LLM-Inspired Sequence-First Click-Through Rate Prediction Modeling Paradigm
Shaopeng Chen, Chuyue Xie, Huimin Ren +11
Traditional Deep Learning Recommendation Models (DLRMs) face increasing bottlenecks in performance and efficiency, often struggling with generalization and long-sequence modeling.…
cs.LG2024
BEFL: Balancing Energy Consumption in Federated Learning for Mobile Edge IoT
Zehao Ju, Tongquan Wei, Fuke Shen
Federated Learning (FL) is a privacy-preserving distributed learning paradigm designed to build a highly accurate global model. In Mobile Edge IoT (MEIoT), the training and communi…