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20242026
most citedInterpreting Chest X-rays Like a Radiologist: A Benchmark with Clinical Reasoning

1 citations · 1 across the 3 of their papers we have counts for

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5 papers

cs.CV2026

Beyond the Global Scores: Fine-Grained Token Grounding as a Robust Detector of LVLM Hallucinations

Tuan Dung Nguyen, Minh Khoi Ho, Qi Chen +8

Large vision-language models (LVLMs) achieve strong performance on visual reasoning tasks but remain highly susceptible to hallucination. Existing detection methods predominantly r…

cs.CV2026

MedObvious: Exposing the Medical Moravec's Paradox in VLMs via Clinical Triage

Ufaq Khan, Umair Nawaz, L D M S S Teja +5

Vision Language Models (VLMs) are increasingly used for tasks like medical report generation and visual question answering. However, fluent diagnostic text does not guarantee safe…

cs.CV20251 cited

Interpreting Chest X-rays Like a Radiologist: A Benchmark with Clinical Reasoning

Jinquan Guan, Qi Chen, Lizhou Liang +5

Artificial intelligence (AI)-based chest X-ray (CXR) interpretation assistants have demonstrated significant progress and are increasingly being applied in clinical settings. Howev…

cs.CV2025

Seeing the Trees for the Forest: Rethinking Weakly-Supervised Medical Visual Grounding

Ta Duc Huy, Duy Anh Huynh, Yutong Xie +10

Visual grounding (VG) is the capability to identify the specific regions in an image associated with a particular text description. In medical imaging, VG enhances interpretability…

cs.CV2024

A Survey of Medical Vision-and-Language Applications and Their Techniques

Qi Chen, Ruoshan Zhao, Sinuo Wang +9

Medical vision-and-language models (MVLMs) have attracted substantial interest due to their capability to offer a natural language interface for interpreting complex medical data.…