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cs.CE2026
HermesHFL: Incentive-Compatible Hierarchical Federated Unlearning for Dynamic LLM Fine-Tuning
Chenxi Sun, Minghui Liwang, Wusi He +5
Hierarchical federated unlearning (HFUL) for large language model (LLM) fine-tuning faces significant challenges due to hierarchical aggregation, dynamic client participation, and…
cs.NI2026
AEGIS: Risk-Budgeted Online Scheduling for Resilient Continuous Edge Inference
Houyi Qi, Minghui Liwang, Sai Zou +2
Continuous edge inference requires sustained wireless and computing support across successive service instances. Under recurring channel degradation, transient edge overload, and m…
cs.NI2026
Masking Intent, Sustaining Equilibrium: Risk-Aware Potential-Game-Based Service Provision in Dynamic Mobile Crowdsensing
Houyi Qi, Minghui Liwang, Kaiwen Tan +5
Mobile crowdsensing (MCS) is evolving from basic data collection to dynamic service provisioning, where platforms must maintain task completion, budget feasibility, and sensing qua…