1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.RO2024★ 1 cited
EM-MIAs: Enhancing Membership Inference Attacks in Large Language Models through Ensemble Modeling
Zichen Song, Sitan Huang, Zhongfeng Kang
With the widespread application of large language models (LLM), concerns about the privacy leakage of model training data have increasingly become a focus. Membership Inference Att…
cs.CL2024★ 1 cited
Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity
Zichen Song, Sitan Huang, Yuxin Wu +1
Evaluating the importance of different layers in large language models (LLMs) is crucial for optimizing model performance and interpretability. This paper first explores layer impo…
cs.CL2024
AVSS: Layer Importance Evaluation in Large Language Models via Activation Variance-Sparsity Analysis
Zichen Song, Yuxin Wu, Sitan Huang +1
The evaluation of layer importance in deep learning has been an active area of research, with significant implications for model optimization and interpretability. Recently, large…