2 citations · 3 across the 10 of their papers we have counts for
5 papers · 1 filter
CLARITY: Medical World Model for Guiding Treatment Decisions by Simulating Context-Aware Disease Trajectories
Tianxingjian Ding, Yuanhao Zou, Chen Chen +2
Clinical decision-making in oncology requires forecasting how disease evolves under treatment, yet most AI systems remain static predictors that cannot model longitudinal, treatmen…
DEXTER: Diffusion-Guided EXplanations with TExtual Reasoning for Vision Models
Simone Carnemolla, Matteo Pennisi, Sarinda Samarasinghe +5
Understanding and explaining the behavior of machine learning models is essential for building transparent and trustworthy AI systems. We introduce DEXTER, a data-free framework th…
From Frames to Clips: Training-free Adaptive Key Clip Selection for Long-Form Video Understanding
Guangyu Sun, Archit Singhal, Burak Uzkent +3
Video Large Language Models (VLMs) have achieved strong performance on various vision-language tasks, yet their practical use is limited by the massive number of visual tokens prod…
Enhancing Privacy-Utility Trade-offs to Mitigate Memorization in Diffusion Models
Chen Chen, Daochang Liu, Mubarak Shah +1
Text-to-image diffusion models have demonstrated remarkable capabilities in creating images highly aligned with user prompts, yet their proclivity for memorizing training set image…
Generative Physical AI in Vision: A Survey
Daochang Liu, Junyu Zhang, Anh-Dung Dinh +5
Generative Artificial Intelligence (AI) has rapidly advanced the field of computer vision by enabling machines to create and interpret visual data with unprecedented sophistication…