7 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)…
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…
When to Invoke: Refining LLM Fairness with Toxicity Assessment
Jing Ren, Bowen Li, Ziqi Xu +6
Large Language Models (LLMs) are increasingly used for toxicity assessment in online moderation systems, where fairness across demographic groups is essential for equitable treatme…
Debiasing Large Language Models via Adaptive Causal Prompting with Sketch-of-Thought
Bowen Li, Ziqi Xu, Jing Ren +5
Despite notable advancements in prompting methods for Large Language Models (LLMs), such as Chain-of-Thought (CoT), existing strategies still suffer from excessive token usage and…
Harnessing LLM for Noise-Robust Cognitive Diagnosis in Web-Based Intelligent Education Systems
Guixian Zhang, Guan Yuan, Ziqi Xu +4
Cognitive diagnostics in the Web-based Intelligent Education System (WIES) aims to assess students' mastery of knowledge concepts from heterogeneous, noisy interactions. Recent wor…
LiteFat: Lightweight Spatio-Temporal Graph Learning for Real-Time Driver Fatigue Detection
Jing Ren, Suyu Ma, Hong Jia +5
Detecting driver fatigue is critical for road safety, as drowsy driving remains a leading cause of traffic accidents. Many existing solutions rely on computationally demanding deep…