4 papers
SCALE: Sensitivity-Aware Federated Unlearning with Information Freshness Optimization for Mobile Edge Computing
Zihao Ding, Beining Wu, Jun Huang
Federated Unlearning (FU) is emerging as a powerful tool that enables the selective removal of client data to effectively address data contamination and meet strict privacy regulat…
ROSE: Rollout On Serving GPUs via Cooperative Elasticity for Agentic RL
Wei Gao, Yuheng Zhao, Dilxat Muhtar +13
Agentic reinforcement learning (RL) is reshaping LLM post-training, but end-to-end training time is dominated by compute-intensive, multi-turn rollouts whose resource demand varies…
PRISM: Exposing and Resolving Spurious Isolation in Federated Multimodal Continual Learning
Beining Wu, Zihao Ding, Jun Huang
While current federated multimodal continual learning over mixture-of-experts low-rank adaptation (MoE-LoRA) is built on the unverified assumption that routing isolates task-specif…
Application-Aware Twin-in-the-Loop Planning for Federated Split Learning over Wireless Edge Networks
Zihao Ding, Beining Wu, Jun Huang +1
We investigate task-success-oriented resource allocation for federated split learning (FSL) at the wireless edge. In this setting, the server must jointly determine bandwidth, tran…