activity
20202026
most citedFedCross: Towards Accurate Federated Learning via Multi-Model Cross-Aggregation

30 citations · 133 across the 49 of their papers we have counts for

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Showing 2024Show all

17 papers · 1 filter

cs.CV2024

Concept Guided Co-salient Object Detection

Jiayi Zhu, Qing Guo, Felix Juefei-Xu +3

Co-salient object detection (Co-SOD) aims to identify common salient objects across a group of related images. While recent methods have made notable progress, they typically rely…

cs.CL2024★ 2 cited

What External Knowledge is Preferred by LLMs? Characterizing and Exploring Chain of Evidence in Imperfect Context for Multi-Hop QA

Zhiyuan Chang, Mingyang Li, Xiaojun Jia +5

Incorporating external knowledge has emerged as a promising way to mitigate outdated knowledge and hallucinations in LLM. However, external knowledge is often imperfect, encompassi…

cs.CR2024★ 1 cited

Heuristic-Induced Multimodal Risk Distribution Jailbreak Attack for Multimodal Large Language Models

Ma Teng, Jia Xiaojun, Duan Ranjie +5

With the rapid advancement of multimodal large language models (MLLMs), concerns regarding their security have increasingly captured the attention of both academia and industry. Al…

cs.CR2024

Global Challenge for Safe and Secure LLMs Track 1

Xiaojun Jia, Yihao Huang, Yang Liu +27

This paper introduces the Global Challenge for Safe and Secure Large Language Models (LLMs), a pioneering initiative organized by AI Singapore (AISG) and the CyberSG R&D Programme…

cs.CV2024★ 1 cited

Semantic-Aligned Adversarial Evolution Triangle for High-Transferability Vision-Language Attack

Xiaojun Jia, Sensen Gao, Qing Guo +6

Vision-language pre-training (VLP) models excel at interpreting both images and text but remain vulnerable to multimodal adversarial examples (AEs). Advancing the generation of tra…

cs.CV2024

Efficient and Effective Universal Adversarial Attack against Vision-Language Pre-training Models

Fan Yang, Yihao Huang, Kailong Wang +4

Vision-language pre-training (VLP) models, trained on large-scale image-text pairs, have become widely used across a variety of downstream vision-and-language (V+L) tasks. This wid…

cs.SE2024★ 1 cited

Understanding the Effectiveness of Coverage Criteria for Large Language Models: A Special Angle from Jailbreak Attacks

Shide Zhou, Tianlin Li, Kailong Wang +4

Large language models (LLMs) have revolutionized artificial intelligence, but their increasing deployment across critical domains has raised concerns about their abnormal behaviors…

cs.CV2024★ 1 cited

HTS-Attack: Heuristic Token Search for Jailbreaking Text-to-Image Models

Sensen Gao, Xiaojun Jia, Yihao Huang +5

Text-to-Image(T2I) models have achieved remarkable success in image generation and editing, yet these models still have many potential issues, particularly in generating inappropri…

cs.CV2024

Perception-guided Jailbreak against Text-to-Image Models

Yihao Huang, Le Liang, Tianlin Li +5

In recent years, Text-to-Image (T2I) models have garnered significant attention due to their remarkable advancements. However, security concerns have emerged due to their potential…

cs.LG2024

NeuSemSlice: Towards Effective DNN Model Maintenance via Neuron-level Semantic Slicing

Shide Zhou, Tianlin Li, Yihao Huang +4

Deep Neural networks (DNNs), extensively applied across diverse disciplines, are characterized by their integrated and monolithic architectures, setting them apart from conventiona…

cs.CV2024

Texture Re-scalable Universal Adversarial Perturbation

Yihao Huang, Qing Guo, Felix Juefei-Xu +5

Universal adversarial perturbation (UAP), also known as image-agnostic perturbation, is a fixed perturbation map that can fool the classifier with high probabilities on arbitrary i…

cs.LG2024★ 3 cited

Improved Techniques for Optimization-Based Jailbreaking on Large Language Models

Xiaojun Jia, Tianyu Pang, Chao Du +5

Large language models (LLMs) are being rapidly developed, and a key component of their widespread deployment is their safety-related alignment. Many red-teaming efforts aim to jail…

cs.CV2024

Text Modality Oriented Image Feature Extraction for Detecting Diffusion-based DeepFake

Di Yang, Yihao Huang, Qing Guo +5

The widespread use of diffusion methods enables the creation of highly realistic images on demand, thereby posing significant risks to the integrity and safety of online informatio…

cs.CL2024★ 1 cited

Efficient Universal Goal Hijacking with Semantics-guided Prompt Organization

Yihao Huang, Chong Wang, Xiaojun Jia +5

Universal goal hijacking is a kind of prompt injection attack that forces LLMs to return a target malicious response for arbitrary normal user prompts. The previous methods achieve…

cs.CV2024

CosalPure: Learning Concept from Group Images for Robust Co-Saliency Detection

Jiayi Zhu, Qing Guo, Felix Juefei-Xu +3

Co-salient object detection (CoSOD) aims to identify the common and salient (usually in the foreground) regions across a given group of images. Although achieving significant progr…

cs.CV2024

MIP: CLIP-based Image Reconstruction from PEFT Gradients

Peiheng Zhou, Ming Hu, Xiaofei Xie +3

Contrastive Language-Image Pre-training (CLIP) model, as an effective pre-trained multimodal neural network, has been widely used in distributed machine learning tasks, especially…

cs.CV2024★ 2 cited

Improving Robustness of LiDAR-Camera Fusion Model against Weather Corruption from Fusion Strategy Perspective

Yihao Huang, Kaiyuan Yu, Qing Guo +5

In recent years, LiDAR-camera fusion models have markedly advanced 3D object detection tasks in autonomous driving. However, their robustness against common weather corruption such…