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cs.CV2024
Charting the Future: Using Chart Question-Answering for Scalable Evaluation of LLM-Driven Data Visualizations
James Ford, Xingmeng Zhao, Dan Schumacher +1
We propose a novel framework that leverages Visual Question Answering (VQA) models to automate the evaluation of LLM-generated data visualizations. Traditional evaluation methods o…
cs.CL2024
Improving Expert Radiology Report Summarization by Prompting Large Language Models with a Layperson Summary
Xingmeng Zhao, Tongnian Wang, Anthony Rios
Radiology report summarization (RRS) is crucial for patient care, requiring concise "Impressions" from detailed "Findings." This paper introduces a novel prompting strategy to enha…