6 papers
EchoPrune: Interpreting Redundancy as Temporal Echoes for Efficient VideoLLMs
Jiameng Li, Minye Wu, Jiezhang Cao +2
Long-form video understanding remains challenging for Video Large Language Models (VideoLLMs), as the dense frame sampling introduces massive visual tokens while sparse sampling ri…
MI-Pruner: Crossmodal Mutual Information-guided Token Pruner for Efficient MLLMs
Jiameng Li, Aleksei Tiulpin, Matthew B. Blaschko
For multimodal large language models (MLLMs), visual information is relatively sparse compared with text. As a result, research on visual pruning emerges for efficient inference. C…
CARE: Confidence-aware Ratio Estimation for Medical Biomarkers
Jiameng Li, Teodora Popordanoska, Aleksei Tiulpin +3
Ratio-based biomarkers (RBBs), such as the proportion of necrotic tissue within a tumor, are widely used in clinical practice to support diagnosis, prognosis, and treatment plannin…
SoftCFG: Uncertainty-guided Stable Guidance for Visual Autoregressive Model
Dongli Xu, Aleksei Tiulpin, Matthew B. Blaschko
Autoregressive (AR) models have emerged as powerful tools for image generation by modeling images as sequences of discrete tokens. While Classifier-Free Guidance (CFG) has been ado…
Bayesian Optimization over Bounded Domains with the Beta Product Kernel
Huy Hoang Nguyen, Han Zhou, Matthew B. Blaschko +1
Bayesian optimization with Gaussian processes (GP) is commonly used to optimize black-box functions. The Matérn and the Radial Basis Function (RBF) covariance functions are used f…
Toward Cost-efficient Adaptive Clinical Trials in Knee Osteoarthritis with Reinforcement Learning
Khanh Nguyen, Huy Hoang Nguyen, Egor Panfilov +1
Osteoarthritis (OA) is the most common musculoskeletal disease, with knee OA (KOA) being one of the leading causes of disability and a significant economic burden. Predicting KOA p…