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 <!-- Background ----------------------------------------------------------->
 <h2>📜 Background</h2>
-<p>Recent advances in <strong>Large Language Models (LLMs)</strong> have demonstrated transformative potential in <strong>healthcare</strong>,  yet concerns remain around their reliability and clinical validity across diverse clinical tasks, specialties, and languages. To support timely and trustworthy evaluation, building upon our <a href="https://ai.nejm.org/doi/full/10.1056/AIra2400012">systematic review</a> of global clinical text resources, we introduce <a href="https://arxiv.org/abs/2504.19467">BRIDGE</a>, <strong>a multilingual benchmark that comprises 87 real-world clinical text tasks spanning nine languages and more than one million samples</strong>. Furthermore, we construct this leaderboard of LLM in clinical text understanding by systematically evaluating <strong>98 state-of-the-art LLMs</strong> (by 2025/11/01).</p>
+<p>Recent advances in <strong>Large Language Models (LLMs)</strong> have demonstrated transformative potential in <strong>healthcare</strong>,  yet concerns remain around their reliability and clinical validity across diverse clinical tasks, specialties, and languages. To support timely and trustworthy evaluation, building upon our <a href="https://ai.nejm.org/doi/full/10.1056/AIra2400012">systematic review</a> of global clinical text resources, we introduce <a href="https://arxiv.org/abs/2504.19467">BRIDGE</a>, <strong>a multilingual benchmark that comprises 87 real-world clinical text tasks spanning nine languages and more than one million samples</strong>. Furthermore, we construct this leaderboard of LLM in clinical text understanding by systematically evaluating <strong>98 state-of-the-art LLMs</strong> (by 2025/11/04).</p>
 This project is led and maintained by the team of <a href="https://ylab.top/">Prof. Jie Yang</a> and <a href="https://www.drugepi.org/team/joshua-kueiyu-lin">Prof. Kueiyu Joshua Lin</a> at Harvard Medical School and Brigham and Women's Hospital. 
 
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