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20242026
most citedPEFTGuard: Detecting Backdoor Attacks Against Parameter-Efficient Fine-Tuning

10 citations · 16 across the 30 of their papers we have counts for

collaborators

34 papers

cs.CV2026

Answer It or Not? Towards Prompt-Adapted Adversarial Images on Vision Language Models

Shunyuan Bai, Yuchen Ren, Le Yang +3

With the advancement in language modeling, research on adversarial images has recently shifted from image classifiers to vision-language models (VLMs). Despite the new, text-prompt…

cs.CV2026

Do Video Generators Track the World Across Segments? A Benchmark and Method for World-State Reasoning in Video Continuation

Yingmao Miao, Pengfei Zhang, Chaoran Xu +5

Video generators build long videos by composing shorter parts, either by generating segments one after another or by autoregressively extending chunks. Each new part usually depend…

cs.CV2026

Detecting Object Hallucinations in Large Vision-Language Models via Cross-Modal Attention Drifts and Mask-Based Verification

Xuanbing Wen, Boxu Chen, Le Yang +4

Despite recent advances in large vision-language models (LVLMs), object hallucination remains a major barrier to their reliable deployment. Existing detection methods often charact…

cs.CV2026

Detecting Backdoors in Object Detection via Pre-NMS Prediction Distribution Shift

Longtian Wang, Zhengyu Zhao, Chenhao Lin +5

Object detection models deployed in safety-critical applications remain vulnerable to backdoor attacks that cause targeted misbehaviors when a hidden trigger is present. Existing d…

cs.SD2026

UOT-IR: Structured Routing of High-Polyphony Symbolic Music into Fixed-Budget Representations

Ziyue Kang, Nan Nan, Chenhao Lin +1

High-polyphony symbolic music is increasingly used in generation, analysis, and arrangement, yet many downstream tasks require bounded representations with fixed tracks or slots. C…

cs.CV2026

Evaluation-Verification Reward for Consistent Multi-Reference Image Editing

Yingmao Miao, Pengfei Zhang, Xiaochen Lv +5

While recent image editing models have made rapid progress, multi-reference editing remains challenging, particularly in maintaining visual consistency across references and ensuri…

cs.CR2026

Alignment Is Local: A Paired Diagnostic for GUI Agents under User-Side Persuasion

Haoxin An, Yunpeng Song, Zihao Bai +6

Trustworthy deployment of GUI agents in ubiquitous computing settings requires alignment that survives dynamic interaction and precise threat conditions, not just single-turn refus…

cs.RO2026

Open-AoE: An Open Egocentric Manipulation Dataset and Toolchain for Embodied Learning

Zishuo Li, Bowen Yang, Changtao Miao +29

Egocentric videos of human manipulation provide scalable supervision for embodied intelligence, yet existing resources rarely combine low-cost continuous capture, manipulation-leve…

cs.CV2026

On Success and Simplicity: A Second Look at Transferable Vision-Language Attack Pipeline

Yuchen Ren, Zhengyu Zhao, Chenhao Lin +2

Vision-Language Pre-training Models (VLPMs) are known to be vulnerable to adversarial attacks. Recent transferable attacks on VLPMs have followed a common pipeline with complicated…

cs.CV2026

CMTA: Leveraging Cross-Modal Temporal Artifacts for Generalizable AI-Generated Video Detection

Hang Wang, Chao Shen, Chenhao Lin +3

The proliferation of advanced AI video synthesis techniques poses an unprecedented challenge to digital video authenticity. Existing AI-generated video (AIGV) detection methods pri…

cs.CV2026

When Understanding Becomes a Risk: Authenticity and Safety Risks in the Emerging Image Generation Paradigm

Ye Leng, Junjie Chu, Mingjie Li +5

Recently, multimodal large language models (MLLMs) have emerged as a unified paradigm for language and image generation. Compared with diffusion models, MLLMs possess a much strong…

cs.LG2025

Pay Less Attention to Function Words for Free Robustness of Vision-Language Models

Qiwei Tian, Chenhao Lin, Zhengyu Zhao +1

To address the trade-off between robustness and performance for robust VLM, we observe that function words could incur vulnerability of VLMs against cross-modal adversarial attacks…

cs.CR2025

GEO-Detective: Unveiling Location Privacy Risks in Images with LLM Agents

Xinyu Zhang, Yixin Wu, Boyang Zhang +4

Images shared on social media often expose geographic cues. While early geolocation methods required expert effort and lacked generalization, the rise of Large Vision Language Mode…

cs.CR2025

Privacy on the Fly: A Predictive Adversarial Transformation Network for Mobile Sensor Data

Tianle Song, Chenhao Lin, Yang Cao +5

Mobile motion sensors such as accelerometers and gyroscopes are now ubiquitously accessible by third-party apps via standard APIs. While enabling rich functionalities like activity…

cs.CV2025

Multi-modal Deepfake Detection and Localization with FPN-Transformer

Chende Zheng, Ruiqi Suo, Zhoulin Ji +4

The rapid advancement of generative adversarial networks (GANs) and diffusion models has enabled the creation of highly realistic deepfake content, posing significant threats to di…

cs.SE2025

Rethinking Technology Stack Selection with AI Coding Proficiency

Xiaoyu Zhang, Weipeng Jiang, Shiqing Ma +5

Large language models (LLMs) are now an integral part of software development workflows and are reshaping the whole process. However, existing technology selection methods mainly f…

cs.CR2025

JADES: A Universal Framework for Jailbreak Assessment via Decompositional Scoring

Junjie Chu, Mingjie Li, Ziqing Yang +6

Accurately determining whether a jailbreak attempt has succeeded is a fundamental yet unresolved challenge. Existing evaluation methods rely on misaligned proxy indicators or naive…

cs.CV2025

Revisiting Adversarial Patch Defenses on Object Detectors: Unified Evaluation, Large-Scale Dataset, and New Insights

Junhao Zheng, Jiahao Sun, Chenhao Lin +6

Developing reliable defenses against patch attacks on object detectors has attracted increasing interest. However, we identify that existing defense evaluations lack a unified and…

cs.CV2025

D3: Training-Free AI-Generated Video Detection Using Second-Order Features

Chende Zheng, Ruiqi suo, Chenhao Lin +6

The evolution of video generation techniques, such as Sora, has made it increasingly easy to produce high-fidelity AI-generated videos, raising public concern over the disseminatio…

cs.CV2025

Adversarial Video Promotion Against Text-to-Video Retrieval

Qiwei Tian, Chenhao Lin, Zhengyu Zhao +3

Thanks to the development of cross-modal models, text-to-video retrieval (T2VR) is advancing rapidly, but its robustness remains largely unexamined. Existing attacks against T2VR a…

cs.CV2025

Concept Unlearning by Modeling Key Steps of Diffusion Process

Chaoshuo Zhang, Chenhao Lin, Zhengyu Zhao +3

Text-to-image diffusion models remain susceptible to generating undesirable or harmful content. Although concept unlearning mitigates this risk, existing methods struggle with a cr…

cs.CR2025

Prediction Inconsistency Helps Achieve Generalizable Detection of Adversarial Examples

Sicong Han, Chenhao Lin, Zhengyu Zhao +6

Adversarial detection protects models from adversarial attacks by refusing suspicious test samples. However, current detection methods often suffer from weak generalization: their…

cs.CV2025

Seeing It or Not? Interpretable Vision-aware Latent Steering to Mitigate Object Hallucinations

Boxu Chen, Ziwei Zheng, Le Yang +4

Large Vision-Language Models (LVLMs) have achieved remarkable success but continue to struggle with object hallucination (OH), generating outputs inconsistent with visual inputs. W…

cs.CV2025

HCMA: Hierarchical Cross-model Alignment for Grounded Text-to-Image Generation

Hang Wang, Zhi-Qi Cheng, Chenhao Lin +2

Text-to-image synthesis has progressed to the point where models can generate visually compelling images from natural language prompts. Yet, existing methods often fail to reconcil…