10 papers
RAGSentinel: Certifiable Geometric Consensus for Robust Retrieval-Augmented Generation
Yueyang Quan, Anjun Gao, Yufei Xia +2
Retrieval-augmented generation (RAG) improves the factuality of large language models by grounding responses in external documents, but it also exposes a critical security vulnerab…
NeuronGuard: Robust LLM Safety Alignment via Ablation-Aware Safety Signal Redistribution
Anjun Gao, Yueyang Quan, Yufei Xia +2
Safety alignment in large language models (LLMs) remains brittle against a growing spectrum of attacks. Jailbreak attacks bypass safety mechanisms through crafted prompts, while ne…
Beware What You Autocomplete: Forensic Attribution of Backdoored Code Completions
Anjun Gao, Yueyang Quan, Zhuqing Liu +1
Large language models have enabled powerful code completion systems that assist developers by predicting subsequent lines of code. However, these models remain vulnerable to backdo…
Who Broke the System? Failure Localization in LLM-Based Multi-Agent Systems
Yufei Xia, Anjun Gao, Yueyang Quan +2
Large language model (LLM) based multi-agent systems enable complex problem solving through coordinated reasoning and action, but their distributed structure also introduces new ch…
Patcher: Post-Hoc Patching of Backdoored Large Language Models
Anjun Gao, Yueyang Quan, Yufei Xia +2
Large language models remain vulnerable to jailbreak backdoor attacks, where adversaries poison safety alignment data to embed hidden triggers that bypass safety mechanisms. Existi…
SecureAFL: Secure Asynchronous Federated Learning
Anjun Gao, Feng Wang, Zhenglin Wan +3
Federated learning (FL) enables multiple clients to collaboratively train a global machine learning model via a server without sharing their private training data. In traditional F…