16 papers
Targeted Downstream-Agnostic Attack
Zhuxin Lei, Ziyuan Yang, Yi Zhang
Recently, pre-trained encoders have gained widespread use due to their strong capability in representation extraction. However, they are vulnerable to downstream-agnostic attacks (…
Whispers in the Noise: Surrogate-Guided Concept Awakening via a Multi-Agent Framework
Mengyu Sun, Ziyuan Yang, Zunlong Zhou +3
Diffusion models (DMs) are widely used for text-to-image generation, but their strong generative capabilities also raise concerns about unsafe or undesirable content. Concept erasu…
Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems
Yue Ma, Ziyuan Yang, Yi Zhang
Large multimodal model-based Multi-Agent Systems (MASs) enable collaborative complex problem solving through specialized agents. However, MASs are vulnerable to infectious jailbrea…
PrismAgent: Illuminating Harm in Memes via a Zero-Shot Interpretable Multi-Agent Framework
Zihan Ding, Ziyuan Yang, Yi Zhang
The rapid spread of memes makes harmful content detection increasingly crucial, as effective identification can curb the circulation of misinformation. However, existing methods re…
From Static Analysis to Audience Dissemination: A Training-Free Multimodal Controversy Detection Multi-Agent Framework
Zihan Ding, Ziyuan Yang, Yi Zhang
Multimodal controversy detection (MCD) identifies controversial content in videos and their associated user comments, to support risk management for social video platforms.Prior re…
Trust the Unreliability: Inward Backward Dynamic Unreliability Driven Coreset Selection for Medical Image Classification
Yan Liang, Ziyuan Yang, Zhuxin Lei +3
Efficiently managing and utilizing large-scale medical imaging datasets with limited resources presents significant challenges. While coreset selection helps reduce computational c…
Code Fingerprints: Disentangled Attribution of LLM-Generated Code
Jiaxun Guo, Ziyuan Yang, Mengyu Sun +3
The rapid adoption of Large Language Models (LLMs) has transformed modern software development by enabling automated code generation at scale. While these systems improve productiv…
Zero-Sacrifice Persistent-Robustness Adversarial Defense for Pre-Trained Encoders
Zhuxin Lei, Ziyuan Yang, Yi Zhang
The widespread use of publicly available pre-trained encoders from self-supervised learning (SSL) has exposed a critical vulnerability: their susceptibility to downstream-agnostic…
Mirage: Transmitting a Video as a Perceptual Illusion for 50,000X Speedup
Junjie Wu, Tianrui Li, Yi Zhang +1
The existing communication framework mainly aims at accurate reconstruction of source signals to ensure reliable transmission. However, this signal-level fidelity-oriented design o…
Hear the Heartbeat in Phases: Physiologically Grounded Phase-Aware ECG Biometrics
Jintao Huang, Lu Leng, Yi Zhang +1
Electrocardiography (ECG) is adopted for identity authentication in wearable devices due to its individual-specific characteristics and inherent liveness. However, existing methods…
Low-Level Dataset Distillation for Medical Image Enhancement
Fengzhi Xu, Ziyuan Yang, Mengyu Sun +2
Medical image enhancement is clinically valuable, but existing methods require large-scale datasets to learn complex pixel-level mappings. However, the substantial training and sto…
Dark Distillation: Backdooring Distilled Datasets without Accessing Raw Data
Ziyuan Yang, Ming Yan, Yi Zhang +1
Dataset distillation (DD) enhances training efficiency and reduces bandwidth by condensing large datasets into smaller synthetic ones. It enables models to achieve performance comp…
FedRIR: Rethinking Information Representation in Federated Learning
Yongqiang Huang, Zerui Shao, Ziyuan Yang +2
Mobile and Web-of-Things (WoT) devices at the network edge generate vast amounts of data for machine learning applications, yet privacy concerns hinder centralized model training.…
Double Banking on Knowledge: Customized Modulation and Prototypes for Multi-Modality Semi-supervised Medical Image Segmentation
Yingyu Chen, Ziyuan Yang, Ming Yan +4
Multi-modality (MM) semi-supervised learning (SSL) based medical image segmentation has recently gained increasing attention for its ability to utilize MM data and reduce reliance…
Trustworthy Hate Speech Detection Through Visual Augmentation
Ziyuan Yang, Ming Yan, Yingyu Chen +3
The surge of hate speech on social media platforms poses a significant challenge, with hate speech detection~(HSD) becoming increasingly critical. Current HSD methods focus on enri…
SynFacePAD 2023: Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data
Meiling Fang, Marco Huber, Julian Fierrez +21
This paper presents a summary of the Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data (SynFacePAD 2023) held at the 2023 Internation…