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MMedPO: Aligning Medical Vision-Language Models with Clinical-Aware Multimodal Preference Optimization
The advancement of Large Vision-Language Models (LVLMs) has propelled their
application in the medical field. However, Medical LVLMs (Med-LVLMs) encounter factuality …
application in the medical field. However, Medical LVLMs (Med-LVLMs) encounter factuality …
ReXErr: Synthesizing Clinically Meaningful Errors in Diagnostic Radiology Reports
Accurately interpreting medical images and writing radiology reports is a critical but
challenging task in healthcare. Both human-written and AI-generated reports can contain …
challenging task in healthcare. Both human-written and AI-generated reports can contain …
TaskGalaxy: Scaling Multi-modal Instruction Fine-tuning with Tens of Thousands Vision Task Types
Multimodal visual language models are gaining prominence in open-world applications,
driven by advancements in model architectures, training techniques, and high-quality data …
driven by advancements in model architectures, training techniques, and high-quality data …
Semantic Consistency-Based Uncertainty Quantification for Factuality in Radiology Report Generation
Radiology report generation (RRG) has shown great potential in assisting radiologists by
automating the labor-intensive task of report writing. While recent advancements have …
automating the labor-intensive task of report writing. While recent advancements have …