1 citations · 1 across the 2 of their papers we have counts for
4 papers
Watermark Robustness and Radioactivity May Be at Odds in Federated Learning
Leixu Huang, Zedian Shao, Teodora Baluta
Federated learning (FL) enables fine-tuning large language models (LLMs) across distributed data sources. As these sources increasingly include LLM-generated text, provenance track…
PromptLocate: Localizing Prompt Injection Attacks
Yuqi Jia, Yupei Liu, Zedian Shao +2
Prompt injection attacks deceive a large language model into completing an attacker-specified task instead of its intended task by contaminating its input data with an injected pro…
A Critical Evaluation of Defenses against Prompt Injection Attacks
Yuqi Jia, Zedian Shao, Yupei Liu +3
Large Language Models (LLMs) are vulnerable to prompt injection attacks, and several defenses have recently been proposed, often claiming to mitigate these attacks successfully. Ho…
WebInject: Prompt Injection Attack to Web Agents
Xilong Wang, John Bloch, Zedian Shao +3
Multi-modal large language model (MLLM)-based web agents interact with webpage environments by generating actions based on screenshots of the webpages. In this work, we propose Web…