10 citations · 20 across the 11 of their papers we have counts for
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Robust Watermarks Meet Backdoored Models: Evading Diffusion Semantic Watermarks via Stealthy Backdoor
Jinyuan Liu, Tianshuo Cong, Pei Li +4
Although semantic watermarking is considered a promising safeguard for images generated by Latent Diffusion Models (LDMs), the reliance of the watermark detection pipeline on neura…
LoRA-Leak: Membership Inference Attacks Against LoRA Fine-tuned Language Models
Delong Ran, Xinlei He, Tianshuo Cong +3
Language Models (LMs) typically adhere to a "pre-training and fine-tuning" paradigm, where a universal pre-trained model can be fine-tuned to cater to various specialized domains.…
Beyond the Tip of Efficiency: Uncovering the Submerged Threats of Jailbreak Attacks in Small Language Models
Sibo Yi, Tianshuo Cong, Xinlei He +2
Small language models (SLMs) have become increasingly prominent in the deployment on edge devices due to their high efficiency and low computational cost. While researchers continu…
CL-Attack: Textual Backdoor Attacks via Cross-Lingual Triggers
Jingyi Zheng, Tianyi Hu, Tianshuo Cong +1
Backdoor attacks significantly compromise the security of large language models by triggering them to output specific and controlled content. Currently, triggers for textual backdo…
PEFTGuard: Detecting Backdoor Attacks Against Parameter-Efficient Fine-Tuning
Zhen Sun, Tianshuo Cong, Yule Liu +5
Fine-tuning is an essential process to improve the performance of Large Language Models (LLMs) in specific domains, with Parameter-Efficient Fine-Tuning (PEFT) gaining popularity d…
Jailbreak Attacks and Defenses Against Large Language Models: A Survey
Sibo Yi, Yule Liu, Zhen Sun +5
Large Language Models (LLMs) have performed exceptionally in various text-generative tasks, including question answering, translation, code completion, etc. However, the over-assis…
On Evaluating The Performance of Watermarked Machine-Generated Texts Under Adversarial Attacks
Zesen Liu, Tianshuo Cong, Xinlei He +1
Large Language Models (LLMs) excel in various applications, including text generation and complex tasks. However, the misuse of LLMs raises concerns about the authenticity and ethi…
JailbreakEval: An Integrated Toolkit for Evaluating Jailbreak Attempts Against Large Language Models
Delong Ran, Jinyuan Liu, Yichen Gong +4
Jailbreak attacks induce Large Language Models (LLMs) to generate harmful responses, posing severe misuse threats. Though research on jailbreak attacks and defenses is emerging, th…
Have You Merged My Model? On The Robustness of Large Language Model IP Protection Methods Against Model Merging
Tianshuo Cong, Delong Ran, Zesen Liu +6
Model merging is a promising lightweight model empowerment technique that does not rely on expensive computing devices (e.g., GPUs) or require the collection of specific training d…