28 citations · 105 across the 18 of their papers we have counts for
4 papers · 1 filter
NAP^2: A Benchmark for Naturalness and Privacy-Preserving Text Rewriting by Learning from Human
Shuo Huang, William MacLean, Xiaoxi Kang +5
The widespread use of cloud-based Large Language Models (LLMs) has heightened concerns over user privacy, as sensitive information may be inadvertently exposed during interactions…
Attacks on Third-Party APIs of Large Language Models
Wanru Zhao, Vidit Khazanchi, Haodi Xing +3
Large language model (LLM) services have recently begun offering a plugin ecosystem to interact with third-party API services. This innovation enhances the capabilities of LLMs, bu…
Generative Models are Self-Watermarked: Declaring Model Authentication through Re-Generation
Aditya Desu, Xuanli He, Qiongkai Xu +1
As machine- and AI-generated content proliferates, protecting the intellectual property of generative models has become imperative, yet verifying data ownership poses formidable ch…
Here's a Free Lunch: Sanitizing Backdoored Models with Model Merge
Ansh Arora, Xuanli He, Maximilian Mozes +3
The democratization of pre-trained language models through open-source initiatives has rapidly advanced innovation and expanded access to cutting-edge technologies. However, this o…