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GLINT: Sparsely Gated Vision-Language Alignment for Fine-Grained Radiology Representations

GLINT introduces sparse gating and dense feature regularization to learn fine-grained radiology vision-language representations that outperform baselines on classification, grounding, and zero-shot 3D CT segmentation.

Jonggwon Park, Seongeun Lee, Junhyun Park, Hannah Yun and 5 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 1/5