12 citations · 15 across the 8 of their papers we have counts for
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cs.CV2026
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…
cs.CV2026
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…
cs.CV2026
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…