8 citations · 11 across the 25 of their papers we have counts for
6 papers · 1 filter
When the Aggregator Cheats: Data-Free Backdoors in Federated LLM-based QA Systems
Chenqing Zhu, Yanbo Dai, Yulong Tian +2
Large Language Model (LLM)-based question-answering (QA) systems are increasingly deployed in sensitive domains such as healthcare, mental health counseling, and legal consultation…
Safety in Self-Evolving LLM Agent Systems: Threats, Amplification, and Case Studies
Ruixiao Lin, Xinhao Deng, Qingming Li +12
Self-evolving LLM agent systems, which autonomously update their model parameters, memory, tools, and architectures, introduce a qualitatively new threat landscape in which adversa…
Understanding and Mitigating Prompt Leaking Attacks in Real-World LLM-Based Applications
Yong Yang, Chong Fu, Tong Zhang +6
Large language model (LLM)-based applications rely on system prompts to encode core logic and developer-defined constraints, making these prompts important intellectual property. H…
Order within Chaos: Capturing Intrinsic Energy Anomalies for AI-Manipulated Image Forgery Localization
Yiming Wang, Baiqi Wu, Qingming Li +3
Recent advancements in generative AI have led to image editing models capable of producing realistic forgeries that evade traditional image forgery localization methods, as these a…
Profiling for Pennies: Unveiling the Privacy Iceberg of LLM Agents
Jiahao Chen, Qi Zhang, Ruixiao Lin +7
Large Language Models (LLMs) have revolutionized how information are collected, aggregated, and reasoned. However, this enables a novel and accessible vector of privacy intrusion:…
Contextual and Seasonal LSTMs for Time Series Anomaly Detection
Lingpei Zhang, Qingming Li, Yong Yang +4
Univariate time series (UTS), where each timestamp records a single variable, serve as crucial indicators in web systems and cloud servers. Anomaly detection in UTS plays an essent…