3 papers
cs.LG2026
Graph Representation Learning Augmented Model Manipulation on Federated Fine-Tuning of LLMs
Hanlin Cai, Kai Li, Houtianfu Wang +4
Federated fine-tuning (FFT) has emerged as a privacy-preserving paradigm for collaboratively adapting large language models (LLMs). Built upon federated learning, FFT enables distr…
cs.NI2026
Graph Representation-based Model Poisoning on the Heterogeneous Internet of Agents
Hanlin Cai, Houtianfu Wang, Haofan Dong +3
Internet of Agents (IoA) envisions a unified, agent-centric paradigm where heterogeneous large language model (LLM) agents can interconnect and collaborate at scale. Within this pa…
cs.CR2025
Graph Representation-based Model Poisoning on Federated Large Language Models
Hanlin Cai, Haofan Dong, Houtianfu Wang +2
Federated large language models (FedLLMs) enable powerful generative capabilities within wireless networks while preserving data privacy. Nonetheless, FedLLMs remain vulnerable to…