9 citations · 9 across the 5 of their papers we have counts for
6 papers
Confidential Error-Correcting Codes
Tianrui Wang, Anyu Wang, Tianshuo Cong +2
We introduce Confidential Error-correcting Codes (CECs), a new cryptographic primitive that enables reliable decoding from perturbed codewords while preserving message confidential…
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…
Cryptanalysis of LDPC-Based Pseudorandom Error-Correcting Codes
Tianrui Wang, Anyu Wang, Tianshuo Cong +3
Pseudorandom error-correcting codes (PRCs), a novel cryptographic primitive recently proposed at CRYPTO 2024, are primarily applied in undetectable watermarking schemes for large g…
One Risk Down, Another Up: Cross-Risk Interactions Induced by LLM Defenses
Xiangtao Meng, Tianshuo Cong, Li Wang +4
Large Language Models (LLMs) are increasingly deployed in high-stakes settings, where they face diverse risks. Numerous defense strategies have been proposed to mitigate these risk…
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…
FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts
Yichen Gong, Delong Ran, Jinyuan Liu +5
Large Vision-Language Models (LVLMs) signify a groundbreaking paradigm shift within the Artificial Intelligence (AI) community, extending beyond the capabilities of Large Language…