10 papers
Stable Multimodal Graph Unlearning via Feature-Dimension Aware Quantile Selection
Jingjing Zhou, Yongshuai Yang, Qing Qing +5
Graph unlearning remains a critical technique for supporting privacy-preserving and sustainable multimodal graph learning. However, we observe that existing unlearning strategies t…
Bridging Semantic Understanding and Popularity Bias with LLMs
Renqiang Luo, Dong Zhang, Yupeng Gao +5
Semantic understanding of popularity bias is a crucial yet underexplored challenge in recommender systems, where popular items are often favored at the expense of niche content. Mo…
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…
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…