Saved in:
| Main Authors: | Zhang, Zhifang, He, Shuo, Wang, Haobo, Shen, Bingquan, Feng, Lei |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2412.20392 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Test-Time Multimodal Backdoor Detection by Contrastive Prompting
by: Niu, Yuwei, et al.
Published: (2024)
by: Niu, Yuwei, et al.
Published: (2024)
Improving Generalizability and Undetectability for Targeted Adversarial Attacks on Multimodal Pre-trained Models
by: Zhang, Zhifang, et al.
Published: (2025)
by: Zhang, Zhifang, et al.
Published: (2025)
Test-Time Attention Purification for Backdoored Large Vision Language Models
by: Zhang, Zhifang, et al.
Published: (2026)
by: Zhang, Zhifang, et al.
Published: (2026)
Correlative and Discriminative Label Grouping for Multi-Label Visual Prompt Tuning
by: Ma, LeiLei, et al.
Published: (2025)
by: Ma, LeiLei, et al.
Published: (2025)
TokenSwap: Backdoor Attack on the Compositional Understanding of Large Vision-Language Models
by: Zhang, Zhifang, et al.
Published: (2025)
by: Zhang, Zhifang, et al.
Published: (2025)
BadBone: Backdoor Attacks Against Backbone Models in Visual Prompt Learning
by: Yang, Ziqing, et al.
Published: (2026)
by: Yang, Ziqing, et al.
Published: (2026)
T2IShield: Defending Against Backdoors on Text-to-Image Diffusion Models
by: Wang, Zhongqi, et al.
Published: (2024)
by: Wang, Zhongqi, et al.
Published: (2024)
Tuning Vision-Language Models with Candidate Labels by Prompt Alignment
by: Zhang, Zhifang, et al.
Published: (2024)
by: Zhang, Zhifang, et al.
Published: (2024)
PromptDx: Differentiable Prompt Tuning for Multimodal In-Context Alzheimer's Diagnosis
by: Zhong, Lujia, et al.
Published: (2026)
by: Zhong, Lujia, et al.
Published: (2026)
FedMVP: Federated Multimodal Visual Prompt Tuning for Vision-Language Models
by: Singha, Mainak, et al.
Published: (2025)
by: Singha, Mainak, et al.
Published: (2025)
Visual Variational Autoencoder Prompt Tuning
by: Xiao, Xi, et al.
Published: (2025)
by: Xiao, Xi, et al.
Published: (2025)
Defending Our Privacy With Backdoors
by: Hintersdorf, Dominik, et al.
Published: (2023)
by: Hintersdorf, Dominik, et al.
Published: (2023)
SecureGaze: Defending Gaze Estimation Against Backdoor Attacks
by: Du, Lingyu, et al.
Published: (2025)
by: Du, Lingyu, et al.
Published: (2025)
Embedded Visual Prompt Tuning
by: Zu, Wenqiang, et al.
Published: (2024)
by: Zu, Wenqiang, et al.
Published: (2024)
Neural Antidote: Class-Wise Prompt Tuning for Purifying Backdoors in CLIP
by: Kong, Jiawei, et al.
Published: (2025)
by: Kong, Jiawei, et al.
Published: (2025)
SEP: Self-Enhanced Prompt Tuning for Visual-Language Model
by: Yao, Hantao, et al.
Published: (2024)
by: Yao, Hantao, et al.
Published: (2024)
Attention to the Burstiness in Visual Prompt Tuning!
by: Wang, Yuzhu, et al.
Published: (2025)
by: Wang, Yuzhu, et al.
Published: (2025)
VPN: Visual Prompt Navigation
by: Feng, Shuo, et al.
Published: (2025)
by: Feng, Shuo, et al.
Published: (2025)
Vision-aware Multimodal Prompt Tuning for Uploadable Multi-source Few-shot Domain Adaptation
by: Liu, Kuanghong, et al.
Published: (2025)
by: Liu, Kuanghong, et al.
Published: (2025)
Defending Text-to-image Diffusion Models: Surprising Efficacy of Textual Perturbations Against Backdoor Attacks
by: Chew, Oscar, et al.
Published: (2024)
by: Chew, Oscar, et al.
Published: (2024)
Revisiting the Power of Prompt for Visual Tuning
by: Wang, Yuzhu, et al.
Published: (2024)
by: Wang, Yuzhu, et al.
Published: (2024)
Visual Instance-aware Prompt Tuning
by: Xiao, Xi, et al.
Published: (2025)
by: Xiao, Xi, et al.
Published: (2025)
Backdoor Attacks on Open Vocabulary Object Detectors via Multi-Modal Prompt Tuning
by: Raj, Ankita, et al.
Published: (2025)
by: Raj, Ankita, et al.
Published: (2025)
Tuned Reverse Distillation: Enhancing Multimodal Industrial Anomaly Detection with Crossmodal Tuners
by: Liu, Xinyue, et al.
Published: (2024)
by: Liu, Xinyue, et al.
Published: (2024)
Efficient Test-Time Prompt Tuning for Vision-Language Models
by: Zhu, Yuhan, et al.
Published: (2024)
by: Zhu, Yuhan, et al.
Published: (2024)
TextlessRAG: End-to-End Visual Document RAG by Speech Without Text
by: Xie, Peijin, et al.
Published: (2025)
by: Xie, Peijin, et al.
Published: (2025)
Backdoor Attacks on Prompt-Driven Video Segmentation Foundation Models
by: Zhang, Zongmin, et al.
Published: (2025)
by: Zhang, Zongmin, et al.
Published: (2025)
VL-Trojan: Multimodal Instruction Backdoor Attacks against Autoregressive Visual Language Models
by: Liang, Jiawei, et al.
Published: (2024)
by: Liang, Jiawei, et al.
Published: (2024)
Visual Fourier Prompt Tuning
by: Zeng, Runjia, et al.
Published: (2024)
by: Zeng, Runjia, et al.
Published: (2024)
Semantic Shield: Defending Vision-Language Models Against Backdooring and Poisoning via Fine-grained Knowledge Alignment
by: Ishmam, Alvi Md, et al.
Published: (2024)
by: Ishmam, Alvi Md, et al.
Published: (2024)
Deep Event-based Object Detection in Autonomous Driving: A Survey
by: Zhou, Bingquan, et al.
Published: (2024)
by: Zhou, Bingquan, et al.
Published: (2024)
Visual Prompt Tuning in Null Space for Continual Learning
by: Lu, Yue, et al.
Published: (2024)
by: Lu, Yue, et al.
Published: (2024)
Instruction Tuning-free Visual Token Complement for Multimodal LLMs
by: Wang, Dongsheng, et al.
Published: (2024)
by: Wang, Dongsheng, et al.
Published: (2024)
GuardT2I: Defending Text-to-Image Models from Adversarial Prompts
by: Yang, Yijun, et al.
Published: (2024)
by: Yang, Yijun, et al.
Published: (2024)
DePT: Decoupled Prompt Tuning
by: Zhang, Ji, et al.
Published: (2023)
by: Zhang, Ji, et al.
Published: (2023)
Facing the Elephant in the Room: Visual Prompt Tuning or Full Finetuning?
by: Han, Cheng, et al.
Published: (2024)
by: Han, Cheng, et al.
Published: (2024)
Exploring Interpretability for Visual Prompt Tuning with Cross-layer Concepts
by: Wang, Yubin, et al.
Published: (2025)
by: Wang, Yubin, et al.
Published: (2025)
CVPT: Cross Visual Prompt Tuning
by: Huang, Lingyun, et al.
Published: (2024)
by: Huang, Lingyun, et al.
Published: (2024)
VP-Bench: A Comprehensive Benchmark for Visual Prompting in Multimodal Large Language Models
by: Xu, Mingjie, et al.
Published: (2025)
by: Xu, Mingjie, et al.
Published: (2025)
Visual Confused Deputy: Exploiting and Defending Perception Failures in Computer-Using Agents
by: Liu, Xunzhuo, et al.
Published: (2026)
by: Liu, Xunzhuo, et al.
Published: (2026)
Similar Items
-
Test-Time Multimodal Backdoor Detection by Contrastive Prompting
by: Niu, Yuwei, et al.
Published: (2024) -
Improving Generalizability and Undetectability for Targeted Adversarial Attacks on Multimodal Pre-trained Models
by: Zhang, Zhifang, et al.
Published: (2025) -
Test-Time Attention Purification for Backdoored Large Vision Language Models
by: Zhang, Zhifang, et al.
Published: (2026) -
Correlative and Discriminative Label Grouping for Multi-Label Visual Prompt Tuning
by: Ma, LeiLei, et al.
Published: (2025) -
TokenSwap: Backdoor Attack on the Compositional Understanding of Large Vision-Language Models
by: Zhang, Zhifang, et al.
Published: (2025)