14 citations · 14 across the 6 of their papers we have counts for
6 papers
MOLM: Mixture of LoRA Markers
Samar Fares, Nurbek Tastan, Noor Hussein +1
Generative models can generate photorealistic images at scale. This raises urgent concerns about the ability to detect synthetically generated images and attribute these images to…
First-Place Solution to NeurIPS 2024 Invisible Watermark Removal Challenge
Fahad Shamshad, Tameem Bakr, Yahia Shaaban +3
Content watermarking is an important tool for the authentication and copyright protection of digital media. However, it is unclear whether existing watermarks are robust against ad…
Mitigating Watermark Forgery in Generative Models via Randomized Key Selection
Toluwani Aremu, Noor Hussein, Munachiso Nwadike +5
Watermarking enables GenAI providers to verify whether content was generated by their models. A watermark is a hidden signal in the content, whose presence can be detected using a…
PromptSmooth: Certifying Robustness of Medical Vision-Language Models via Prompt Learning
Noor Hussein, Fahad Shamshad, Muzammal Naseer +1
Medical vision-language models (Med-VLMs) trained on large datasets of medical image-text pairs and later fine-tuned for specific tasks have emerged as a mainstream paradigm in med…
Multi-Attribute Vision Transformers are Efficient and Robust Learners
Hanan Gani, Nada Saadi, Noor Hussein +1
Since their inception, Vision Transformers (ViTs) have emerged as a compelling alternative to Convolutional Neural Networks (CNNs) across a wide spectrum of tasks. ViTs exhibit not…
Align Your Prompts: Test-Time Prompting with Distribution Alignment for Zero-Shot Generalization
Jameel Hassan, Hanan Gani, Noor Hussein +4
The promising zero-shot generalization of vision-language models such as CLIP has led to their adoption using prompt learning for numerous downstream tasks. Previous works have sho…