7 papers
CLARITY: Medical World Model for Guiding Treatment Decisions by Modeling Context-Aware Disease Trajectories in Latent Space
Tianxingjian Ding, Yuanhao Zou, Chen Chen +2
Clinical decision-making in oncology requires predicting dynamic disease evolution, a task current static AI predictors cannot perform. While world models (WMs) offer a paradigm fo…
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…
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…
Curriculum Direct Preference Optimization for Diffusion and Consistency Models
Florinel-Alin Croitoru, Vlad Hondru, Radu Tudor Ionescu +2
Direct Preference Optimization (DPO) has been proposed as an effective and efficient alternative to reinforcement learning from human feedback (RLHF). In this paper, we propose a n…
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…
Investigating Memorization in Video Diffusion Models
Chen Chen, Enhuai Liu, Daochang Liu +2
Diffusion models, widely used for image and video generation, face a significant limitation: the risk of memorizing and reproducing training data during inference, potentially gene…