3 papers
cs.CL2025
StepChain GraphRAG: Reasoning Over Knowledge Graphs for Multi-Hop Question Answering
Tengjun Ni, Xin Yuan, Shenghong Li +4
Recent progress in retrieval-augmented generation (RAG) has led to more accurate and interpretable multi-hop question answering (QA). Yet, challenges persist in integrating iterati…
cs.LG2023
Data-Agnostic Model Poisoning against Federated Learning: A Graph Autoencoder Approach
Kai Li, Jingjing Zheng, Xin Yuan +3
This paper proposes a novel, data-agnostic, model poisoning attack on Federated Learning (FL), by designing a new adversarial graph autoencoder (GAE)-based framework. The attack re…
eess.SP2023
OFDMA-FL: Federated Learning With Flexible Aggregation Over an OFDMA Air Interface
Shuyan Hu, Xin Yuan, Wei Ni +3
Federated learning (FL) can suffer from a communication bottleneck when deployed in mobile networks, limiting participating clients and deterring FL convergence. The impact of prac…