4 papers · 1 filter
In-Context Probing for Membership Inference in Fine-Tuned Language Models
Zhexi Lu, Hongliang Chi, Nathalie Baracaldo +3
Membership inference attacks (MIAs) pose a critical privacy threat to fine-tuned large language models (LLMs), especially when models are adapted to domain-specific tasks using sen…
Diagnosing and Addressing Pitfalls in KG-RAG Datasets: Toward More Reliable Benchmarking
Liangliang Zhang, Zhuorui Jiang, Hongliang Chi +8
Knowledge Graph Question Answering (KGQA) systems rely on high-quality benchmarks to evaluate complex multi-hop reasoning. However, despite their widespread use, popular datasets s…
Shapley-Guided Utility Learning for Effective Graph Inference Data Valuation
Hongliang Chi, Qiong Wu, Zhengyi Zhou +1
Graph Neural Networks (GNNs) have demonstrated remarkable performance in various graph-based machine learning tasks, yet evaluating the importance of neighbors of testing nodes rem…
Unifying and Optimizing Data Values for Selection via Sequential Decision-Making
Hongliang Chi, Qiong Wu, Zhengyi Zhou +3
Data selection has emerged as a crucial downstream application of data valuation, yet the theoretical foundations for using data values in selection remain underexplored. We reform…