2 citations · 4 across the 13 of their papers we have counts for
4 papers · 1 filter
Vulnerability-Aware Alignment: Mitigating Uneven Forgetting in Harmful Fine-Tuning
Liang Chen, Xueting Han, Li Shen +2
Harmful fine-tuning (HFT), performed directly on open-source LLMs or through Fine-tuning-as-a-Service, breaks safety alignment and poses significant threats. Existing methods aim t…
Time-aware Graph Structure Learning via Sequence Prediction on Temporal Graphs
Haozhen Zhang, Xueting Han, Xi Xiao +1
Temporal Graph Learning, which aims to model the time-evolving nature of graphs, has gained increasing attention and achieved remarkable performance recently. However, in reality,…
AdapterGNN: Parameter-Efficient Fine-Tuning Improves Generalization in GNNs
Shengrui Li, Xueting Han, Jing Bai
Fine-tuning pre-trained models has recently yielded remarkable performance gains in graph neural networks (GNNs). In addition to pre-training techniques, inspired by the latest wor…
Adaptive Transfer Learning on Graph Neural Networks
Xueting Han, Zhenhuan Huang, Bang An +1
Graph neural networks (GNNs) is widely used to learn a powerful representation of graph-structured data. Recent work demonstrates that transferring knowledge from self-supervised t…