25 citations · 33 across the 8 of their papers we have counts for
8 papers
LLM Watermarking as Big Data Provenance: A Deployment-Oriented Systematization
Huy Phan, Kieu Dang, Ojaswi Dulal +4
As large language models (LLMs) become widely deployed, their outputs can be copied, transformed, and redistributed at scale without reliable evidence of origin, creating risks for…
EcoSpa: Efficient Transformer Training with Coupled Sparsity
Jinqi Xiao, Cheng Luo, Lingyi Huang +8
Transformers have become the backbone of modern AI, yet their high computational demands pose critical system challenges. While sparse training offers efficiency gains, existing me…
DisDet: Exploring Detectability of Backdoor Attack on Diffusion Models
Yang Sui, Huy Phan, Jinqi Xiao +6
In the exciting generative AI era, the diffusion model has emerged as a very powerful and widely adopted content generation and editing tool for various data modalities, making the…
ELRT: Efficient Low-Rank Training for Compact Convolutional Neural Networks
Yang Sui, Miao Yin, Yu Gong +3
Low-rank compression, a popular model compression technique that produces compact convolutional neural networks (CNNs) with low rankness, has been well-studied in the literature. O…
CSTAR: Towards Compact and STructured Deep Neural Networks with Adversarial Robustness
Huy Phan, Miao Yin, Yang Sui +2
Model compression and model defense for deep neural networks (DNNs) have been extensively and individually studied. Considering the co-importance of model compactness and robustnes…
RIBAC: Towards Robust and Imperceptible Backdoor Attack against Compact DNN
Huy Phan, Cong Shi, Yi Xie +7
Recently backdoor attack has become an emerging threat to the security of deep neural network (DNN) models. To date, most of the existing studies focus on backdoor attack against t…