3 citations · 3 across the 10 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
LoG-VMamba: Local-Global Vision Mamba for Medical Image Segmentation
Trung Dinh Quoc Dang, Huy Hoang Nguyen, Aleksei Tiulpin
Mamba, a State Space Model (SSM), has recently shown competitive performance to Convolutional Neural Networks (CNNs) and Transformers in Natural Language Processing and general seq…
KNEEL: Knee Anatomical Landmark Localization Using Hourglass Networks
Aleksei Tiulpin, Iaroslav Melekhov, Simo Saarakkala
This paper addresses the challenge of localization of anatomical landmarks in knee X-ray images at different stages of osteoarthritis (OA). Landmark localization can be viewed as r…
Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data
Aleksei Tiulpin, Stefan Klein, Sita M. A. Bierma-Zeinstra +5
Knee osteoarthritis (OA) is the most common musculoskeletal disease without a cure, and current treatment options are limited to symptomatic relief. Prediction of OA progression is…