3 papers
cs.NI2026
HyGra: Accelerating Network-State Simulation for LLM Training in DCNs via Adaptive Packet-Flow Granularity
Wenyi Wang, Zheng Wu, Yanmeng Wang +4
In recent years, large language models (LLMs) have driven substantial intelligent transformation across diverse industries. Commercial LLM training is typically performed over data…
cs.DC2025
Robust Federated Fine-Tuning in Heterogeneous Networks with Unreliable Connections: An Aggregation View
Yanmeng Wang, Zhiwen Dai, Shuai Wang +4
Federated Fine-Tuning (FFT) has attracted growing interest as it leverages both server- and client-side data to enhance global model generalization while preserving privacy, and si…
cs.DC2025
Robust Federated Learning in Unreliable Wireless Networks: A Client Selection Approach
Yanmeng Wang, Wenkai Ji, Jian Zhou +2
Federated learning (FL) has emerged as a promising distributed learning paradigm for training deep neural networks (DNNs) at the wireless edge, but its performance can be severely…