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20242026
most citedPrompt-Guided Internal States for Hallucination Detection of Large Language Models

1 citations · 1 across the 10 of their papers we have counts for

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cs.CR2025

Practical Framework for Privacy-Preserving and Byzantine-robust Federated Learning

Baolei Zhang, Minghong Fang, Zhuqing Liu +5

Federated Learning (FL) allows multiple clients to collaboratively train a model without sharing their private data. However, FL is vulnerable to Byzantine attacks, where adversari…

cs.CR2025

Who Taught the Lie? Responsibility Attribution for Poisoned Knowledge in Retrieval-Augmented Generation

Baolei Zhang, Haoran Xin, Yuxi Chen +6

Retrieval-Augmented Generation (RAG) integrates external knowledge into large language models to improve response quality. However, recent work has shown that RAG systems are highl…

cs.CR2025

Probe before You Talk: Towards Black-box Defense against Backdoor Unalignment for Large Language Models

Biao Yi, Tiansheng Huang, Sishuo Chen +4

Backdoor unalignment attacks against Large Language Models (LLMs) enable the stealthy compromise of safety alignment using a hidden trigger while evading normal safety auditing. Th…

cs.CR2025

CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning

Biao Yi, Tiansheng Huang, Baolei Zhang +4

Fine-tuning-as-a-service, while commercially successful for Large Language Model (LLM) providers, exposes models to harmful fine-tuning attacks. As a widely explored defense paradi…

cs.CR2025

Hiding in Plain Sight: A Steganographic Approach to Stealthy LLM Jailbreaks

Jianing Geng, Biao Yi, Zekun Fei +4

Jailbreak attacks pose a serious threat to Large Language Models (LLMs) by bypassing their safety mechanisms. A truly advanced jailbreak is defined not only by its effectiveness bu…

cs.CR2025

Traceback of Poisoning Attacks to Retrieval-Augmented Generation

Baolei Zhang, Haoran Xin, Minghong Fang +4

Large language models (LLMs) integrated with retrieval-augmented generation (RAG) systems improve accuracy by leveraging external knowledge sources. However, recent research has re…

cs.CR2024

Your Semantic-Independent Watermark is Fragile: A Semantic Perturbation Attack against EaaS Watermark

Zekun Fei, Biao Yi, Jianing Geng +3

Embedding-as-a-Service (EaaS) has emerged as a successful business pattern but faces significant challenges related to various forms of copyright infringement, particularly, the AP…

cs.CR2024

BadActs: A Universal Backdoor Defense in the Activation Space

Biao Yi, Sishuo Chen, Yiming Li +3

Backdoor attacks pose an increasingly severe security threat to Deep Neural Networks (DNNs) during their development stage. In response, backdoor sample purification has emerged as…