most citedUnderstanding Multi-Turn Toxic Behaviors in Open-Domain Chatbots

17 citations · 33 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR20231 cited

Jailbreaker in Jail: Moving Target Defense for Large Language Models

Bocheng Chen, Advait Paliwal, Qiben Yan

Large language models (LLMs), known for their capability in understanding and following instructions, are vulnerable to adversarial attacks. Researchers have found that current com…

cs.CR20231 cited

PhantomSound: Black-Box, Query-Efficient Audio Adversarial Attack via Split-Second Phoneme Injection

Hanqing Guo, Guangjing Wang, Yuanda Wang +3

In this paper, we propose PhantomSound, a query-efficient black-box attack toward voice assistants. Existing black-box adversarial attacks on voice assistants either apply substitu…

cs.DC2023

DynamicFL: Balancing Communication Dynamics and Client Manipulation for Federated Learning

Bocheng Chen, Nikolay Ivanov, Guangjing Wang +1

Federated Learning (FL) is a distributed machine learning (ML) paradigm, aiming to train a global model by exploiting the decentralized data across millions of edge devices. Compar…

cs.CR202317 cited

Understanding Multi-Turn Toxic Behaviors in Open-Domain Chatbots

Bocheng Chen, Guangjing Wang, Hanqing Guo +2

Recent advances in natural language processing and machine learning have led to the development of chatbot models, such as ChatGPT, that can engage in conversational dialogue with…

cs.SD202314 cited

VSMask: Defending Against Voice Synthesis Attack via Real-Time Predictive Perturbation

Yuanda Wang, Hanqing Guo, Guangjing Wang +2

Deep learning based voice synthesis technology generates artificial human-like speeches, which has been used in deepfakes or identity theft attacks. Existing defense mechanisms inj…