1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2026
SeaCausal-FL: Federated Fuzzy Causal Learning for Maritime IoT Fault Diagnosis and Counterfactual Reasoning
Yuhang Qiu, Haihan Zhu, Koteeswaran Seerangan +6
Reliable marine-engine fault diagnosis in maritime IoT is challenged by distributed data ownership, heterogeneous fault distributions, and continuously changing operating condition…
cs.LG2026
Conflict-Aware Federated Fine-Tuning of Large Language Models with Mixture-of-Experts
Yijun Lu, Zihan Fang, Pengpeng Qiao +6
The continuous scaling of large language models (LLMs) incurs prohibitive computational costs, making Mixture-of-Experts (MoE) a scalable alternative for efficient fine-tuning via…
cs.NI2025★ 1 cited
SFL-LEO: Asynchronous Split-Federated Learning Design for LEO Satellite-Ground Network Framework
Jiasheng Wu, Jingjing Zhang, Zheng Lin +4
Recently, the rapid development of LEO satellite networks spurs another widespread concern-data processing at satellites. However, achieving efficient computation at LEO satellites…