When LoRA Betrays: Backdooring Text-to-Image Models by Masquerading as Benign Adapters
cs.CV
Submitted: 2026-02-25
Updated: 2026-04-24
Comments: Accepted to CVPR 2026 main track(poster)
Journal ref: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026
Code: https://github.com/spectreinit/MasqLora
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Causal-Guided Detoxify Backdoor Attack of Open-Weight LoRA Models
- LoRATK: LoRA Once, Backdoor Everywhere in the Share-and-Play Ecosystem
- BAAAN: Backdoor Attacks Against Autoencoder and GAN-Based Machine Learning Models
- LoBAM: LoRA-Based Backdoor Attack on Model Merging
Related papers
- Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
- AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
- Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
- MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
- TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
- A Survey on Efficient Vision-Language-Action Models