66 citations · 188 across the 33 of their papers we have counts for
34 papers
MultiAnimate: A Unified Framework for Controllable Multi-Character Animation
Zhongyi Zhang, Guangyuan Wang, Li Hu +6
Recent advances in generative models and technological innovations have significantly addressed the fundamental challenges of character image animation. However, existing approache…
VLMShield: Efficient and Robust Defense of Vision-Language Models against Malicious Prompts
Peigui Qi, Kunsheng Tang, Yanpu Yu +7
Vision-Language Models (VLMs) face significant safety vulnerabilities from malicious prompt attacks due to weakened alignment during visual integration. Existing defenses suffer fr…
State-Dependent Safety Failures in Multi-Turn Language Model Interaction
Pengcheng Li, Jie Zhang, Tianwei Zhang +5
Safety alignment in large language models is typically evaluated under isolated queries, yet real-world use is inherently multi-turn. Although multi-turn jailbreaks are empirically…
Rethinking Multi-Condition DiTs: Eliminating Redundant Attention via Position-Alignment and Keyword-Scoping
Chao Zhou, Tianyi Wei, Yiling Chen +2
While modern text-to-image models excel at prompt-based generation, they often lack the fine-grained control necessary for specific user requirements like spatial layouts or subjec…
Character as a Latent Variable in Large Language Models: A Mechanistic Account of Emergent Misalignment and Conditional Safety Failures
Yanghao Su, Wenbo Zhou, Tianwei Zhang +4
Emergent Misalignment refers to a failure mode in which fine-tuning large language models (LLMs) on narrowly scoped data induces broadly misaligned behavior. Prior explanations mai…
GUIGuard-Bench: Toward a General Evaluation for Privacy-Preserving GUI Agents
Yanxi Wang, Zhiling Zhang, Wenbo Zhou +6
As GUI agents increasingly rely on screenshots to perceive and operate digital environments, they may inadvertently expose sensitive information such as identities, accounts, locat…
MF-Speech: Achieving Fine-Grained and Compositional Control in Speech Generation via Factor Disentanglement
Xinyue Yu, Youqing Fang, Pingyu Wu +4
Generating expressive and controllable human speech is one of the core goals of generative artificial intelligence, but its progress has long been constrained by two fundamental ch…
SafeGuider: Robust and Practical Content Safety Control for Text-to-Image Models
Peigui Qi, Kunsheng Tang, Wenbo Zhou +5
Text-to-image models have shown remarkable capabilities in generating high-quality images from natural language descriptions. However, these models are highly vulnerable to adversa…
Beyond Sliders: Mastering the Art of Diffusion-based Image Manipulation
Yufei Tang, Daiheng Gao, Pingyu Wu +3
In the realm of image generation, the quest for realism and customization has never been more pressing. While existing methods like concept sliders have made strides, they often fa…
PoseGuard: Pose-Guided Generation with Safety Guardrails
Kongxin Wang, Jie Zhang, Peigui Qi +3
Pose-guided video generation has become a powerful tool in creative industries, exemplified by frameworks like Animate Anyone. However, conditioning generation on specific poses in…
BURN: Backdoor Unlearning via Adversarial Boundary Analysis
Yanghao Su, Jie Zhang, Yiming Li +6
Backdoor unlearning aims to remove backdoor-related information while preserving the model's original functionality. However, existing unlearning methods mainly focus on recovering…
CasaGPT: Cuboid Arrangement and Scene Assembly for Interior Design
Weitao Feng, Hang Zhou, Jing Liao +2
We present a novel approach for indoor scene synthesis, which learns to arrange decomposed cuboid primitives to represent 3D objects within a scene. Unlike conventional methods tha…
MES-RAG: Bringing Multi-modal, Entity-Storage, and Secure Enhancements to RAG
Pingyu Wu, Daiheng Gao, Jing Tang +4
Retrieval-Augmented Generation (RAG) improves Large Language Models (LLMs) by using external knowledge, but it struggles with precise entity information retrieval. In this paper, w…
FaceTracer: Unveiling Source Identities from Swapped Face Images and Videos for Fraud Prevention
Zhongyi Zhang, Jie Zhang, Wenbo Zhou +5
Face-swapping techniques have advanced rapidly with the evolution of deep learning, leading to widespread use and growing concerns about potential misuse, especially in cases of fr…
GenderCARE: A Comprehensive Framework for Assessing and Reducing Gender Bias in Large Language Models
Kunsheng Tang, Wenbo Zhou, Jie Zhang +7
Large language models (LLMs) have exhibited remarkable capabilities in natural language generation, but they have also been observed to magnify societal biases, particularly those…
UniForensics: Face Forgery Detection via General Facial Representation
Ziyuan Fang, Hanqing Zhao, Tianyi Wei +5
Previous deepfake detection methods mostly depend on low-level textural features vulnerable to perturbations and fall short of detecting unseen forgery methods. In contrast, high-l…
Rank-based No-reference Quality Assessment for Face Swapping
Xinghui Zhou, Wenbo Zhou, Tianyi Wei +5
Face swapping has become a prominent research area in computer vision and image processing due to rapid technological advancements. The metric of measuring the quality in most face…
AquaLoRA: Toward White-box Protection for Customized Stable Diffusion Models via Watermark LoRA
Weitao Feng, Wenbo Zhou, Jiyan He +6
Diffusion models have achieved remarkable success in generating high-quality images. Recently, the open-source models represented by Stable Diffusion (SD) are thriving and are acce…
Controlling risks of AI in chemical science with agents
Jiyan He, Weitao Feng, Haoxiang Guan +11
Artificial intelligence is rapidly advancing scientific discovery, but this progress carries risks of misuse, such as the creation of harmful substances, or circumvention of establ…
Segue: Side-information Guided Generative Unlearnable Examples for Facial Privacy Protection in Real World
Zhiling Zhang, Jie Zhang, Kui Zhang +3
The widespread use of face recognition technology has given rise to privacy concerns, as many individuals are worried about the collection and utilization of their facial data. To…
HairCLIPv2: Unifying Hair Editing via Proxy Feature Blending
Tianyi Wei, Dongdong Chen, Wenbo Zhou +4
Hair editing has made tremendous progress in recent years. Early hair editing methods use well-drawn sketches or masks to specify the editing conditions. Even though they can enabl…
Catch You Everything Everywhere: Guarding Textual Inversion via Concept Watermarking
Weitao Feng, Jiyan He, Jie Zhang +4
AIGC (AI-Generated Content) has achieved tremendous success in many applications such as text-to-image tasks, where the model can generate high-quality images with diverse prompts,…
X-Adv: Physical Adversarial Object Attacks against X-ray Prohibited Item Detection
Aishan Liu, Jun Guo, Jiakai Wang +6
Adversarial attacks are valuable for evaluating the robustness of deep learning models. Existing attacks are primarily conducted on the visible light spectrum (e.g., pixel-wise tex…
X-Paste: Revisiting Scalable Copy-Paste for Instance Segmentation using CLIP and StableDiffusion
Hanqing Zhao, Dianmo Sheng, Jianmin Bao +9
Copy-Paste is a simple and effective data augmentation strategy for instance segmentation. By randomly pasting object instances onto new background images, it creates new training…