2 citations · 2 across the 11 of their papers we have counts for
9 papers · 1 filter
LoRango: It Takes Two LoRAs to Unlock Hidden Behaviors in Diffusion Models
Jin Wei, Rundong Li, Ruihao Yang +10
Users commonly combine multiple Low-Rank Adaptation (LoRA) adapters to personalize images with different subjects, styles, and visual attributes. Yet inspecting adapters individual…
Detecting and Localizing Segment-Level Poisoning in Multi-Source LLM-Agent Inputs
Xue Tan, Changhui Wang, Sanrui Yang +6
Modern large language model (LLM) agents often construct prompts by aggregating retrieved passages, user reviews, and documents from multiple external sources. This paradigm expose…
ViTeGate: Visual-Textual Triggered Knowledge Poisoning for Vision-Language Retrieval-Augmented Generation
Xue Tan, Xuandi Zeng, Yu Shao +5
Modern Vision-Language Retrieval-Augmented Generation (VLRAG) systems augment Large Vision-Language Models (LVLMs) with retrieved visual and textual evidence, enabling responses gr…
PixCrypt: Fast Fine-Grained FHE with Range-Aware Caching
Chao Wang, Shubing Yang, Xiaoyan Sun +3
Many analytics tasks require secure computation over encrypted data. In particular, fine-grained data such as pixel-level images require higher precision, as every pixel can direct…
A Trustworthy Watermarking Framework for LLM-Generated Food Safety Content
Zhongli Fang, Yiran Chen, Lingyun Zhang +4
Large language models are transforming many industries with their text generation abilities. However, their outputs can be easily tampered with, creating serious risks in critical…
Measuring the Wrong Thing: Internal Harmfulness Scores Anti-Rank Successful Jailbreaks
Mingyu Luo, Ming Deng, Zilang Qiu +8
Internal safety scores judge a prompt before any text is generated, and they are validated by how well they separate harmful prompts from benign ones. That separation is then read…
When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems
Haowen Xu, Xue Tan, Lei Ma +6
While enabling effective collaboration on complex tasks, LLM-based Multi-Agent Systems (MAS) face critical security challenges due to vulnerabilities at the agent and interaction l…
PRA-RAG: Provably Robust Aggregation in Retrieval-Augmented Generation against Retrieval Corruption
Xue Tan, Yi Zheng, Chang Huo +7
Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by incorporating external knowledge, effectively mitigating their inherent knowledge limitations. However…
Generalizable and Interpretable RF Fingerprinting with Shapelet-Enhanced Large Language Models
Tianya Zhao, Junqing Zhang, Haowen Xu +3
Deep neural networks (DNNs) have achieved remarkable success in radio frequency (RF) fingerprinting for wireless device authentication. However, their practical deployment faces tw…