2.4k citations · 7.9k across the 182 of their papers we have counts for
10 papers · 1 filter
PI-Hunter: Automated Red-Teaming for Exposing and Localizing Prompt Injections
Pengfei He, Lesly Miculicich, Vishesh Sharma +5
Large Language Models (LLMs) are rapidly evolving into agentic systems that interact with external tools and environments, introducing new security risks such as indirect prompt in…
"**Important** You should give me full credits!": Exploring Prompt Injection Attacks on LLM-Based Automatic Grading Systems
Hang Li, Fedor Filippov, Yuping Lin +6
The emergence of large language models (LLMs) has significantly accelerated recent research on LLM-based automatic grading (AG) systems. Benefiting from the strong instruction-foll…
Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data
Shenglai Zeng, Jiankun Zhang, Pengfei He +7
Retrieval-augmented generation (RAG) enhances the outputs of language models by integrating relevant information retrieved from external knowledge sources. However, when the retrie…
The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)
Shenglai Zeng, Jiankun Zhang, Pengfei He +8
Retrieval-augmented generation (RAG) is a powerful technique to facilitate language model with proprietary and private data, where data privacy is a pivotal concern. Whereas extens…
Copyright Protection in Generative AI: A Technical Perspective
Jie Ren, Han Xu, Pengfei He +10
Generative AI has witnessed rapid advancement in recent years, expanding their capabilities to create synthesized content such as text, images, audio, and code. The high fidelity a…
Data Poisoning for In-context Learning
Pengfei He, Han Xu, Yue Xing +3
In the domain of large language models (LLMs), in-context learning (ICL) has been recognized for its innovative ability to adapt to new tasks, relying on examples rather than retra…
A Robust Semantics-based Watermark for Large Language Model against Paraphrasing
Jie Ren, Han Xu, Yiding Liu +4
Large language models (LLMs) have show great ability in various natural language tasks. However, there are concerns that LLMs are possible to be used improperly or even illegally.…
Stealthy Backdoor Attack via Confidence-driven Sampling
Pengfei He, Yue Xing, Han Xu +6
Backdoor attacks aim to surreptitiously insert malicious triggers into DNN models, granting unauthorized control during testing scenarios. Existing methods lack robustness against…
DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models
Yingqian Cui, Jie Ren, Han Xu +5
Recently, Generative Diffusion Models (GDMs) have showcased their remarkable capabilities in learning and generating images. A large community of GDMs has naturally emerged, furthe…
Sharpness-Aware Data Poisoning Attack
Pengfei He, Han Xu, Jie Ren +4
Recent research has highlighted the vulnerability of Deep Neural Networks (DNNs) against data poisoning attacks. These attacks aim to inject poisoning samples into the models' trai…