12 citations · 15 across the 8 of their papers we have counts for
4 papers · 1 filter
What Do Visual-Head Discovery Scores Actually Find? Attention Source, Necessity, and Random-Control Pitfalls in Vision-Language Models
Md Abdul Kadir, Daniel Sonntag
Attention heads that attend to image regions relevant to a question are increasingly used to steer, ground and interpret vision-language models (VLMs) and to reduce their hallucina…
Beyond Heatmaps: Unsupervised Concept-Graph Reasoning for Interpretable Visual Explanation
Md Mohasin Hossain, Anar Amirli, Robert Leist +2
Concept Bottleneck Models (CBMs) provide an intrinsically interpretable alternative to post-hoc explanations. However, existing CBMs often rely on predefined concept vocabularies o…
TRACE: A Concept Bottleneck Model for Longitudinal 3D Glioblastoma Response Assessment
Alia Tarek, Hamsa Saberr, Hamza Elghonemy +6
Longitudinal glioblastoma response assessment requires comparing subtle tumor changes across MRI time points using structured clinical criteria such as RANO. However, most deep lea…
Modular Deep Active Learning Framework for Image Annotation: A Technical Report for the Ophthalmo-AI Project
Md Abdul Kadir, Hasan Md Tusfiqur Alam, Pascale Maul +3
Image annotation is one of the most essential tasks for guaranteeing proper treatment for patients and tracking progress over the course of therapy in the field of medical imaging…