32 citations · 60 across the 8 of their papers we have counts for
9 papers
EAVer: Long-Form Factuality Verification as an End-to-End Agentic Policy
Kening Zheng, Aoying Zheng, Zhigang Chang +21
Long-form factuality verification is commonly implemented as a static decompose-search-verify pipeline, with separately prompted modules processing claims and invoking external sea…
Beyond Vector Hiding: Breaking and Mitigating Shared-Direction Weight Obfuscation in TEE-Offloaded Large Language Models
Menghui Zhang, Aoying Zheng, Guoxiao Liu +4
Trusted Execution Environment (TEE)-shielded partitioning of Large Language Models (LLMs) accelerates on-device inference by offloading obfuscated linear layers to an untrusted acc…
FlipGuard: Defending Large Language Models Against Quantization-Conditioned Backdoor Attacks
Aoying Zheng, Anqi Du, Zizhuang Deng +1
Model quantization is essential for the efficient deployment of Large Language Models (LLMs), but introduces a critical vulnerability: Quantization-Conditioned Backdoor (QCB) attac…
QuantGuard: Learnable Rounding for Repairing Quantization-Conditioned Backdoors in LLMs
Aoying Zheng, Anqi Du, Zizhuang Deng +3
Model quantization is a key technique for reducing storage and inference costs in large language model deployment. However, recent studies show that the discretization and rounding…
PlanGuard: Defending Agents against Indirect Prompt Injection via Planning-based Consistency Verification
Guangyu Gong, Zizhuang Deng
Large Language Model (LLM) agents are increasingly integrated into critical systems, leveraging external tools to interact with the real world. However, this capability exposes the…
HLPD: Aligning LLMs to Human Language Preference for Machine-Revised Text Detection
Fangqi Dai, Xingjian Jiang, Zizhuang Deng
To prevent misinformation and social issues arising from trustworthy-looking content generated by LLMs, it is crucial to develop efficient and reliable methods for identifying the…
The Art of Hide and Seek: Making Pickle-Based Model Supply Chain Poisoning Stealthy Again
Tong Liu, Guozhu Meng, Peng Zhou +3
Pickle deserialization vulnerabilities have persisted throughout Python's history, remaining widely recognized yet unresolved. Due to its ability to transparently save and restore…
Demystifying RCE Vulnerabilities in LLM-Integrated Apps
Tong Liu, Zizhuang Deng, Guozhu Meng +2
LLMs show promise in transforming software development, with a growing interest in integrating them into more intelligent apps. Frameworks like LangChain aid LLM-integrated app dev…
Understanding Real-world Threats to Deep Learning Models in Android Apps
Zizhuang Deng, Kai Chen, Guozhu Meng +3
Famous for its superior performance, deep learning (DL) has been popularly used within many applications, which also at the same time attracts various threats to the models. One pr…