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cs.CV2025

Robust Multimodal Learning via Cross-Modal Proxy Tokens

Md Kaykobad Reza, Ameya Patil, Mashhour Solh +1

Multimodal models often experience a significant performance drop when one or more modalities are missing during inference. To address this challenge, we propose a simple yet effec…

cs.CL2025

Cross-Modal Safety Alignment: Is textual unlearning all you need?

Trishna Chakraborty, Erfan Shayegani, Zikui Cai +5

Recent studies reveal that integrating new modalities into Large Language Models (LLMs), such as Vision-Language Models (VLMs), creates a new attack surface that bypasses existing…

cs.CV2025

EigenScore: OOD Detection using Covariance in Diffusion Models

Shirin Shoushtari, Yi Wang, Xiao Shi +2

Out-of-distribution (OOD) detection is critical for the safe deployment of machine learning systems in safety-sensitive domains. Diffusion models have recently emerged as powerful…

eess.IV2025

Gaussian is All You Need: A Unified Framework for Solving Inverse Problems via Diffusion Posterior Sampling

Nebiyou Yismaw, Ulugbek S. Kamilov, M. Salman Asif

Diffusion models can generate a variety of high-quality images by modeling complex data distributions. Trained diffusion models can also be very effective image priors for solving…

cs.CV2025

VOccl3D: A Video Benchmark Dataset for 3D Human Pose and Shape Estimation under real Occlusions

Yash Garg, Saketh Bachu, Arindam Dutta +5

Human pose and shape (HPS) estimation methods have been extensively studied, with many demonstrating high zero-shot performance on in-the-wild images and videos. However, these met…

cs.LG2025

Targeted Unlearning with Single Layer Unlearning Gradient

Zikui Cai, Yaoteng Tan, M. Salman Asif

Machine unlearning methods aim to remove sensitive or unwanted content from trained models, but typically demand extensive model updates at significant computational cost while pot…