4 citations · 20 across the 34 of their papers we have counts for
35 papers
PhyCheck: Fine-Grained Evidence-Grounded Dataset for Physical Law Understanding in Video-LLMs
Zhongjie Ba, Shengwang Xu, Peng Cheng +4
Embodied intelligence and world models require video understanding systems to go beyond recognizing objects and actions and develop an understanding of physical regularities. Howev…
Inverting the Hidden: Unveiling Multimodal Privacy Leakage in Collaborative LVLM Inference
Shuaifan Jin, Zhibo Wang, Qiyuan Wang +5
Collaborative inference deploys Large Vision-Language Models (LVLMs) by partitioning computation between edge devices and the cloud. While withholding raw inputs supposedly ensures…
From Role Prompt to Infinite Thinking: Exploiting Persona Conditioning for Inference Cost Attacks in LLMs
Zhiyi Mou, Wangze Ni, Tianfang Xiao +6
LLMs are increasingly deployed in real-world applications, making inference efficiency and service reliability critical concerns due to their substantial computational costs. Howev…
Attention-Free and Lightweight Token Reduction for Efficient Vision-Language Models
Xuanyi Hao, Zuoyuan Zhang, Zhibo Wang +4
Vision-Language Models (VLMs) have achieved strong performance in multimodal understanding, yet remain challenging to deploy on resource-constrained edge devices due to the substan…
LoRA-Key: User-Centric LoRA Watermarking for Text-to-Image Diffusion Models
Yaopeng Wang, Qingliang Wang, Zhibo Wang +5
Low-Rank Adaptation (LoRA) has become a widely used mechanism for customizing text-to-image diffusion models, enabling lightweight modules that are shared, reused, and commercializ…
LoopTrap: Termination Poisoning Attacks on LLM Agents
Huiyu Xu, Zhibo Wang, Wenhui Zhang +4
Modern LLM agents solve complex tasks by operating in iterative execution loops, where they repeatedly reason, act, and self-evaluate progress to determine when a task is complete.…
RouteScan: A Non-Intrusive Approach to Auditing MoE LLMs Safety via Expert Routing Telemetry
Bo Lv, Zhiheng Xu, KeDong Xiu +4
As Mixture-of-Experts (MoE) architectures are increasingly adopted for scaling Large Language Models (LLMs), safety auditing becomes necessary to verify whether these models produc…
APPSI-139: A Parallel Corpus of English Application Privacy Policy Summarization and Interpretation
Pengyun Zhu, Qiheng Sun, Long Wen +7
Privacy policies are essential for users to understand how service providers handle their personal data. However, these documents are often long and complex, as well as filled with…
DualSentinel: A Lightweight Framework for Detecting Targeted Attacks in Black-box LLM via Dual Entropy Lull Pattern
Xiaoyi Pang, Xuanyi Hao, Pengyu Liu +3
Recent intelligent systems integrate powerful Large Language Models (LLMs) through APIs, but their trustworthiness may be critically undermined by targeted attacks like backdoor an…
RerouteGuard: Understanding and Mitigating Adversarial Risks for LLM Routing
Wenhui Zhang, Huiyu Xu, Zhibo Wang +4
Recent advancements in multi-model AI systems have leveraged LLM routers to reduce computational cost while maintaining response quality by assigning queries to the most appropriat…
RBD: A Reconstruction-Based Method for Generalizable and Efficient Detection of Fake Images
Qingyu Liu, Zhongjie Ba, Jianmin Guo +4
Recently, reconstruction-based methods have gained attention for AIGC image detection. These methods leverage pre-trained diffusion models to reconstruct inputs and measure residua…
Attack-Resistant Watermarking for AIGC Image Forensics via Diffusion-based Semantic Deflection
Qingyu Liu, Yitao Zhang, Zhongjie Ba +4
Protecting the copyright of user-generated AI images is an emerging challenge as AIGC becomes pervasive in creative workflows. Existing watermarking methods (1) remain vulnerable t…
TAP-ViTs: Task-Adaptive Pruning for On-Device Deployment of Vision Transformers
Zhibo Wang, Zuoyuan Zhang, Xiaoyi Pang +4
Vision Transformers (ViTs) have demonstrated strong performance across a wide range of vision tasks, yet their substantial computational and memory demands hinder efficient deploym…
PromptCOS: Towards Content-only System Prompt Copyright Auditing for LLMs
Yuchen Yang, Yiming Li, Hongwei Yao +6
System prompts are critical for shaping the behavior and output quality of large language model (LLM)-based applications, driving substantial investment in optimizing high-quality…
AFLoRA: Adaptive Federated Fine-Tuning of Large Language Models with Resource-Aware Low-Rank Adaption
Yajie Zhou, Xiaoyi Pang, Zhibo Wang
Federated fine-tuning has emerged as a promising approach to adapt foundation models to downstream tasks using decentralized data. However, real-world deployment remains challengin…
PRUNE: A Patching Based Repair Framework for Certifiable Unlearning of Neural Networks
Xuran Li, Jingyi Wang, Xiaohan Yuan +1
It is often desirable to remove (a.k.a. unlearn) a specific part of the training data from a trained neural network model. A typical application scenario is to protect the data hol…
PT-Mark: Invisible Watermarking for Text-to-image Diffusion Models via Semantic-aware Pivotal Tuning
Yaopeng Wang, Huiyu Xu, Zhibo Wang +5
Watermarking for diffusion images has drawn considerable attention due to the widespread use of text-to-image diffusion models and the increasing need for their copyright protectio…
Interpretable LLM Guardrails via Sparse Representation Steering
Zeqing He, Zhibo Wang, Huiyu Xu +3
Large language models (LLMs) exhibit impressive capabilities in generation tasks but are prone to producing harmful, misleading, or biased content, posing significant ethical and s…
Privacy-Preserving LLM Embedding Transmission for End-Cloud Collaboration
Shuaifan Jin, Xiaoyi Pang, Zhibo Wang +4
Recent studies improve on-device language model (LM) inference through end-cloud collaboration, where the end device retrieves useful information from cloud databases to enhance lo…
Can Small Language Models Reliably Resist Jailbreak Attacks? A Comprehensive Evaluation
Zhibo Wang, Wenhui Zhang, Huiyu Xu +3
Small language models (SLMs) have emerged as promising alternatives to large language models (LLMs) due to their low computational demands, enhanced privacy guarantees, and compara…
Hiding Faces in Plain Sight: Defending DeepFakes by Disrupting Face Detection
Delong Zhu, Yuezun Li, Baoyuan Wu +3
Face-swapping DeepFakes have become an escalating societal concern, attracting increasing attention in recent years. To counter this, we investigate a new proactive defense framewo…
JailbreakLens: Interpreting Jailbreak Mechanism in the Lens of Representation and Circuit
Zeqing He, Zhibo Wang, Zhixuan Chu +4
Despite the outstanding performance of Large language Models (LLMs) in diverse tasks, they are vulnerable to jailbreak attacks, wherein adversarial prompts are crafted to bypass th…
PointNCBW: Towards Dataset Ownership Verification for Point Clouds via Negative Clean-label Backdoor Watermark
Cheng Wei, Yang Wang, Kuofeng Gao +4
Recently, point clouds have been widely used in computer vision, whereas their collection is time-consuming and expensive. As such, point cloud datasets are the valuable intellectu…
RedAgent: Red Teaming Large Language Models with Context-aware Autonomous Language Agent
Huiyu Xu, Wenhui Zhang, Zhibo Wang +5
Recently, advanced Large Language Models (LLMs) such as GPT-4 have been integrated into many real-world applications like Code Copilot. These applications have significantly expand…