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Somayeh Ebrahimkhani

2 accepted papers

2026

How Do Medical MLLMs Fail? A Study on Visual Grounding in Medical Images

ICLR 2026poster

Generalist multimodal large language models (MLLMs) have achieved impressive performance across a wide range of vision-language tasks. However, their performance on medical tasks—particularly in zero-shot settings where generalization is critical—remains suboptimal. A key research gap is the limited…

Cited by 0SourceScholar
2024

Vision Transformer Neural Architecture Search for Out-of-Distribution Generalization: Benchmark and Insights

NeurIPS 2024poster

While Vision Transformer (ViT) have achieved success across various machine learning tasks, deploying them in real-world scenarios faces a critical challenge: generalizing under Out-of-Distribution (OoD) shifts. A crucial research gap remains in understanding how to design ViT architectures – both m…