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most citedRobust-LLaVA: On the Effectiveness of Large-Scale Robust Image Encoders for Multi-modal Large Language Models

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cs.CR2025

SPQR: A Multi-Dimensional Benchmark for Safety Alignment under Benign Model Adaptation

Mohammed Talha Alam, Nada Saadi, Fahad Shamshad +4

Text-to-image diffusion models can emit copyrighted, unsafe, or private content. Safety alignment aims to suppress specific concepts, yet evaluations seldom test whether safety per…

cs.CV2025

Calibration-Aware Prompt Learning for Medical Vision-Language Models

Abhishek Basu, Fahad Shamshad, Ashshak Sharifdeen +2

Medical Vision-Language Models (Med-VLMs) have demonstrated remarkable performance across diverse medical imaging tasks by leveraging large-scale image-text pretraining. However, t…

cs.CV2025

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…

cs.CV2025

FaceAnonyMixer: Cancelable Faces via Identity Consistent Latent Space Mixing

Mohammed Talha Alam, Fahad Shamshad, Fakhri Karray +1

Advancements in face recognition (FR) technologies have amplified privacy concerns, necessitating methods that protect identity while maintaining recognition utility. Existing face…

cs.CV2025★ 1 cited

Robust-LLaVA: On the Effectiveness of Large-Scale Robust Image Encoders for Multi-modal Large Language Models

Hashmat Shadab Malik, Fahad Shamshad, Muzammal Naseer +3

Multi-modal Large Language Models (MLLMs) excel in vision-language tasks but remain vulnerable to visual adversarial perturbations that can induce hallucinations, manipulate respon…