1 citations · 1 across the 30 of their papers we have counts for
32 papers
Runaway Reaction: When Benign Skills Compose into Malicious Behavior
Zunlong Zhou, Ziyuan Yang, Mengyu Sun +1
Agent skills package task-specific knowledge and procedures that can be composed to support complex agent tasks, while public marketplaces provide a growing pool of reusable skills…
The Error You See Is Not the Error You Made: Progression-aware Reasoning Origin for Reasoning Error Localization
Yiguo Wang, Ziyuan Yang, Yi Zou +3
Verifying multi-step LLM reasoning requires more than determining whether a trace is correct: a useful verifier should identify where the reasoning first goes wrong. However, exist…
One-Time Training for All Grains: Open-Set Grain Recognition and Quantitative Analysis
Qihe Su, Mengyu Sun, Yuxi Ke +4
Advances in crop breeding have introduced an increasing number of grain varieties, creating a growing demand for efficient variety recognition and quantitative analysis. However, e…
EvoOMG: An Evolution-Oriented Multi-Agent Guidance Framework for Heterogeneous Legacy-and-MLO Wi-Fi Networks
Junjie Wu, Lingjian Zhou, Zerui Shao +4
The gradual deployment of Wi-Fi 7/8 multi-link operation (MLO) will lead to long-term coexistence between legacy non-MLO stations (STAs) and MLO-capable STAs in WLANs. This mixed d…
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…
From Compression to Accountability: Harmless Copyright Protection for Dataset Distillation
Yan Liang, Ziyuan Yang, Mengyu Sun +2
Large-scale datasets have been a key driving force behind the rapid progress of deep learning, but their storage, computational, and energy costs have become increasingly prohibiti…
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…
PRISM: Refracting the Entangled User Behavior Space for E-Commerce Search
Haoqian Zhang, Ziyuan Yang, Yi Zhang
E-commerce search systems rely on modeling user behavior to estimate item relevance and user preference, which are typically assumed to be stable and independently learnable signal…
Asymmetric Invertible Threat: Learning Reversible Privacy Defense for Face Recognition
Jiabei Zhang, Ziyuan Yang, Andrew Beng Jin Teoh +1
Face Recognition systems are widely deployed in real-world applications, but they also raise privacy concerns due to unauthorized collection and misuse of facial data. Existing adv…
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…
One CT Unified Model Training Framework to Rule All Scanning Protocols
Fengzhi Xu, Ziyuan Yang, Zexin Lu +4
Non-ideal measurement computed tomography (NICT), which lowers radiation at the cost of image quality, is expanding the clinical use of CT. Although unified models have shown promi…
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…
PalmBridge: A Plug-and-Play Feature Alignment Framework for Open-Set Palmprint Verification
Chenke Zhang, Ziyuan Yang, Licheng Yan +4
Palmprint recognition is widely used in biometric systems, yet real-world performance often degrades due to feature distribution shifts caused by heterogeneous deployment condition…
LURE: Latent Space Unblocking for Multi-Concept Reawakening in Diffusion Models
Mengyu Sun, Ziyuan Yang, Andrew Beng Jin Teoh +3
Concept erasure aims to suppress sensitive content in diffusion models, but recent studies show that erased concepts can still be reawakened, revealing vulnerabilities in erasure m…
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…
Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval
Yi Xie, Ziyuan Yang, Yongqiang Huang +4
Android malware detection continues to face persistent challenges stemming from long-term concept drift and class imbalance, as evolving malicious behaviors and shifting usage patt…
Federated Learning for Large Models in Medical Imaging: A Comprehensive Review
Mengyu Sun, Ziyuan Yang, Yongqiang Huang +5
Artificial intelligence (AI) has demonstrated considerable potential in the realm of medical imaging. However, the development of high-performance AI models typically necessitates…
Patient-Level Anatomy Meets Scanning-Level Physics: Personalized Federated Low-Dose CT Denoising Empowered by Large Language Model
Ziyuan Yang, Yingyu Chen, Zhiwen Wang +3
Reducing radiation doses benefits patients, however, the resultant low-dose computed tomography (LDCT) images often suffer from clinically unacceptable noise and artifacts. While d…