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Dongxiao Zhu

6 papers indexed here

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#artificial intelligence Preprint Sep 2026

SpatialCORE: Confidence-Aware Grounded Spatial Reasoning in Large Vision--Language Models

Large Vision-Language Models (LVLMs) have made remarkable progress across visual perception tasks, yet spatial reasoning remains a persistent weakness, especially for questions that require reasoning over visual space. Recent spatial-reasoning methods incorporate generated grounding, where models predict bounding boxes...

Rafi Ibn Sultan, Xiang-Yu Zhou, Mohammad O. S. Chowdhury et al. · 0 citations
Open access Aug 2026

A neighborhood attention transformer network for enhanced 3D segmentation of the left anterior descending artery.

BACKGROUND Accurate segmentation of the left anterior descending (LAD) artery in 3D free-breathing, non-contrast CT is critical for cardiac dose sparing in thoracic radiotherapy. The task is inherently difficult because the LAD is extremely small, exhibits poor soft-tissue contrast, and varies substantially across pati...

Rafi Ibn Sultan, Chengyin Li, Yiannos Demetriou et al. · 1 citation
Open access Sep 2026

Cross-fraction prior learning for scalable organ-at-risk segmentation in abdominal MR-guided radiotherapy.

BACKGROUND Manual organ-at-risk (OAR) delineation takes 20-40 min per case, a major bottleneck within the 50-90 min treatment window of abdominal MR-guided adaptive radiotherapy (MRgRT). Most deep learning systems adopt single-fraction approaches that discard valuable temporal context from prior treatment fractions....

Chengyin Li, D. Rusu, Rafi Ibn Sultan et al. · 0 citations
Preprint Aug 2026

MedPlex: Deep Vision-Language Co-Adaptation for Clinically Grounded Medical Segmentation

Medical image segmentation is still largely treated as a vision-only problem, although clinical interpretation often relies on textual knowledge of anatomy, location, appearance, and surrounding context. Existing text-guided segmentation methods within the Vision-Language Model (VLM) paradigm often use language only as...

Rafi Ibn Sultan, Hui Zhu, Chengyin Li et al. · 0 citations
#artificial intelligence Preprint Aug 2026

Partition-Aware Unlearning for Removing Spurious Correlations in Large Vision-Language Models

The results show that PURGE consistently reduces hallucinations and spurious-correlation-driven errors while maintaining or improving overall performance in most evaluated settings, providing both a reusable evaluation protocol and an effective mitigation framework for more reliable LVLMs.

Aditi Sarker, Nazreen Shah, Rafi Ibn Sultan et al. · 0 citations

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