9 papers
When to Trust: A Causality-Aware Calibration Framework for Accurate Knowledge Graph Retrieval-Augmented Generation
Jing Ren, Bowen Li, Ziqi Xu +3
Knowledge Graph Retrieval-Augmented Generation (KG-RAG) extends the RAG paradigm by incorporating structured knowledge from knowledge graphs, enabling Large Language Models (LLMs)…
FedCARE: Federated Unlearning with Conflict-Aware Projection and Relearning-Resistant Recovery
Yue Li, Mingmin Chu, Xilei Yang +5
Federated learning (FL) enables collaborative model training without centralizing raw data, but privacy regulations such as the right to be forgotten require FL systems to remove t…
Securing LLM-as-a-Service for Small Businesses: An Industry Case Study of a Distributed Chatbot Deployment Platform
Jiazhu Xie, Bowen Li, Heyu Fu +3
Large Language Model (LLM)-based question-answering systems offer significant potential for automating customer support and internal knowledge access in small businesses, yet their…
FairGU: Fairness-aware Graph Unlearning in Social Networks
Renqiang Luo, Yongshuai Yang, Huafei Huang +6
Graph unlearning has emerged as a critical mechanism for supporting sustainable and privacy-preserving social networks, enabling models to remove the influence of deleted nodes and…
FairGE: Fairness-Aware Graph Encoding in Incomplete Social Networks
Renqiang Luo, Huafei Huang, Tao Tang +5
Graph Transformers (GTs) are increasingly applied to social network analysis, yet their deployment is often constrained by fairness concerns. This issue is particularly critical in…
STEAMROLLER: A Multi-Agent System for Inclusive Automatic Speech Recognition for People who Stutter
Ziqi Xu, Yi Liu, Yuekang Li +3
People who stutter (PWS) face systemic exclusion in today's voice-driven society, where access to voice assistants, authentication systems, and remote work tools increasingly depen…