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<p class="MsoNormal"><i><span style="font-family:"Arial",sans-serif;color:#570606">UNIVERSITY OF CHICAGO</span></i><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
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<i><span style="font-family:"Arial",sans-serif;color:#570606">COMPUTER SCIENCE DEPARTMENT</span></i><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
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<i><span style="font-family:"Arial",sans-serif;color:#570606">PRESENTS</span></i><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
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<b><span style="font-size:12.0pt;font-family:"Aptos",sans-serif;color:black">Hejie Cu<o:p></o:p></span></b></p>
<p class="MsoNormal"><b><span style="font-family:"Arial",sans-serif;color:black;background:white">Postdoctoral Scholar
</span></b><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
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<b><span style="font-family:"Arial",sans-serif;color:black">Stanford University </span>
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<b><span style="font-family:"Arial",sans-serif;color:black">Thursday,<span class="apple-converted-space"> </span>February 6<sup>th</sup>, 2025</span></b><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
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<b><span style="font-family:"Arial",sans-serif;color:black">2:00PM – 3:00PM CT . </span>
</b><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
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<b><span style="font-family:"Arial",sans-serif;color:black">Location : TTIC 530<br>
Zoom Link :<span class="apple-converted-space"> <a href="https://uchicago.zoom.us/j/97708787366?pwd=qD9KdtzwGCTPuciAfr6iaap3NubZgy.1">Click Here
</a></span></span></b><span style="font-size:10.0pt;color:black"> <o:p></o:p></span></p>
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<b><span style="font-family:"Arial",sans-serif;color:black">Title:<span class="apple-converted-space"> </span></span></b><b><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:#242424;background:white">Empowering Medical LLMs: Holistic Evaluation
and Clinician-Guided Instruction Tuning</span></b><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
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<b><span style="font-family:"Arial",sans-serif;color:black">Abstract</span></b><span style="font-family:"Arial",sans-serif;color:black">:<span class="apple-converted-space"> </span></span><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:#242424;background:white">Recent
advancements in large language models (LLMs) and multimodal foundation models have shown remarkable potential for transforming healthcare applications. While these models demonstrate impressive performance on standardized medical exams, their real-world clinical
utility remains underexplored. This talk presents two complementary frameworks addressing critical gaps in medical AI development and evaluation. First, we introduce a comprehensive benchmarking framework for evaluating LLMs across 121 healthcare tasks derived
from clinician-validated taxonomies. Unlike existing evaluations that rely primarily on standardized tests, this framework assesses model performance on real-world medical scenarios: clinical decision support, note generation, patient communication, research
assistance, and administrative workflows. Second, we present a novel data-centric approach that incorporates clinician preferences into biomedical visual instruction tuning. By integrating expert knowledge in both data generation and selection processes, this
method produces high-quality instruction datasets that significantly enhance model performance in visual medical tasks. Together, these frameworks advance the field toward more clinically relevant and trustworthy AI systems for healthcare applications.</span><span style="font-size:10.0pt;font-family:"Arial",sans-serif;color:black"><o:p></o:p></span></p>
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<b><span style="font-family:"Arial",sans-serif;color:black">Bio</span></b><span style="font-family:"Arial",sans-serif;color:black">:</span><span class="apple-converted-space"><span style="font-size:10.0pt;font-family:"Arial",sans-serif;color:black"> </span></span><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:black;background:white">Hejie
is a Postdoctoral Scholar working on AI for Healthcare and Trustworthy Machine Learning at Stanford University. Her research interests focuses on Large Language Model (LLM) Evaluation and Post-training for Healthcare. </span><span style="font-size:10.0pt;font-family:"Arial",sans-serif;color:black"><o:p></o:p></span></p>
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<span style="font-family:"Arial",sans-serif;color:black"> </span><span style="font-family:"Arial",sans-serif;color:black;mso-ligatures:none"><img border="0" width="270" height="270" style="width:2.8125in;height:2.8125in" id="Picture_x0020_2" src="cid:image001.jpg@01DB8796.FAFF4880" alt="Hejie Cui"></span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
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