8 citations · 9 across the 11 of their papers we have counts for
13 papers
MPCEval: A Benchmark for Multi-Party Conversation Generation
Minxing Zhang, Yi Yang, Zhuofan Jia +5
Multi-party conversation generation, such as smart reply and collaborative assistants, is an increasingly important capability of generative AI, yet its evaluation remains a critic…
Learning to Attack: Uncovering Privacy Risks in Sequential Data Releases
Ziyao Cui, Minxing Zhang, Jian Pei
Privacy concerns have become increasingly critical in modern AI and data science applications, where sensitive information is collected, analyzed, and shared across diverse domains…
Generalizability of Large Language Model-Based Agents: A Comprehensive Survey
Minxing Zhang, Yi Yang, Roy Xie +3
Large Language Model (LLM)-based agents have emerged as a new paradigm that extends LLMs' capabilities beyond text generation to dynamic interaction with external environments. By…
On Membership Inference Attacks in Knowledge Distillation
Ziyao Cui, Minxing Zhang, Jian Pei
Large language models (LLMs) are trained on massive corpora that may contain sensitive information, creating privacy risks under membership inference attacks (MIAs). Knowledge dist…
DivTrackee versus DynTracker: Promoting Diversity in Anti-Facial Recognition against Dynamic FR Strategy
Wenshu Fan, Minxing Zhang, Hongwei Li +5
The widespread adoption of facial recognition (FR) models raises serious concerns about their potential misuse, motivating the development of anti-facial recognition (AFR) to prote…
Invisibility Cloak: Disappearance under Human Pose Estimation via Backdoor Attacks
Minxing Zhang, Wenshu Fan, Wenbo Jiang +3
Despite being significant in autonomous systems, Human Pose Estimation (HPE)'s potential risks to adversarial attacks have not received comparable attention with image classificati…
Vera Verto: Multimodal Hijacking Attack
Minxing Zhang, Ahmed Salem, Michael Backes +1
The increasing cost of training machine learning (ML) models has led to the inclusion of new parties to the training pipeline, such as users who contribute training data and compan…
Protecting Data Buyer Privacy in Data Markets
Minxing Zhang, Jian Pei
Data markets serve as crucial platforms facilitating data discovery, exchange, sharing, and integration among data users and providers. However, the paramount concern of privacy ha…
ReCaLL: Membership Inference via Relative Conditional Log-Likelihoods
Roy Xie, Junlin Wang, Ruomin Huang +5
The rapid scaling of large language models (LLMs) has raised concerns about the transparency and fair use of the data used in their pretraining. Detecting such content is challengi…
Generated Distributions Are All You Need for Membership Inference Attacks Against Generative Models
Minxing Zhang, Ning Yu, Rui Wen +2
Generative models have demonstrated revolutionary success in various visual creation tasks, but in the meantime, they have been exposed to the threat of leaking private information…
Generating Less Certain Adversarial Examples Improves Robust Generalization
Minxing Zhang, Michael Backes, Xiao Zhang
This paper revisits the robust overfitting phenomenon of adversarial training. Observing that models with better robust generalization performance are less certain in predicting ad…
Graph Neural Network for spatiotemporal data: methods and applications
Yun Li, Dazhou Yu, Zhenke Liu +3
In the era of big data, there has been a surge in the availability of data containing rich spatial and temporal information, offering valuable insights into dynamic systems and pro…
Membership Inference Attacks Against Recommender Systems
Minxing Zhang, Zhaochun Ren, Zihan Wang +4
Recently, recommender systems have achieved promising performances and become one of the most widely used web applications. However, recommender systems are often trained on highly…