1 citations · 1 across the 7 of their papers we have counts for
8 papers
SSCL-BW: Sample-Specific Clean-Label Backdoor Watermarking for Dataset Ownership Verification
Yingjia Wang, Ting Qiao, Xing Liu +3
The rapid advancement of deep neural networks (DNNs) heavily relies on large-scale, high-quality datasets. However, unauthorized commercial use of these datasets severely violates…
PromptMap: Supporting Exploratory Text-to-Image Generation
Yuhan Guo, Xingyou Liu, Xiaoru Yuan +1
Text-to-image generative models can be tremendously valuable in supporting creative tasks by providing inspirations and enabling quick exploration of different design ideas. Howeve…
DSSmoothing: Toward Certified Dataset Ownership Verification for Pre-trained Language Models via Dual-Space Smoothing
Ting Qiao, Xing Liu, Wenke Huang +3
Large web-scale datasets have driven the rapid advancement of pre-trained language models (PLMs), but unauthorized data usage has raised serious copyright concerns. Existing datase…
Breaking Android with AI: A Deep Dive into LLM-Powered Exploitation
Wanni Vidulige Ishan Perera, Xing Liu, Fan liang +1
The rapid evolution of Artificial Intelligence (AI) and Large Language Models (LLMs) has opened up new opportunities in the area of cybersecurity, especially in the exploitation au…
Counterfactual Segmentation Reasoning: Diagnosing and Mitigating Pixel-Grounding Hallucination
Xinzhuo Li, Adheesh Juvekar, Jiaxun Zhang +6
Segmentation Vision-Language Models (VLMs) have significantly advanced grounded visual understanding, yet they remain prone to pixel-grounding hallucinations, producing masks for i…
Cert-SSBD: Certified Backdoor Defense with Sample-Specific Smoothing Noises
Ting Qiao, Yingjia Wang, Xing Liu +3
Deep neural networks (DNNs) are vulnerable to backdoor attacks, where an attacker manipulates a small portion of the training data to implant hidden backdoors into the model. The c…
INFELM: In-depth Fairness Evaluation of Large Text-To-Image Models
Di Jin, Xing Liu, Yu Liu +7
The rapid development of large language models (LLMs) and large vision models (LVMs) have propelled the evolution of multi-modal AI systems, which have demonstrated the remarkable…
On the Robustness of Kernel Goodness-of-Fit Tests
Xing Liu, François-Xavier Briol
Goodness-of-fit testing is often criticized for its lack of practical relevance: since ``all models are wrong'', the null hypothesis that the data conform to our model is ultimatel…