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Exploring and Distilling Posterior and Prior Knowledge for Radiology Report Generation

CVPR 2021 · Vision-language and multimodal › Human and embodied modeling · approach: Medical vision-language models · 346 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use PPKED instead of R2GenRadiology report generation · MIMIC-CXRBLEU-1: 0.353 -> 0.360Helped
Use PPKED instead of R2GenRadiology report generation · IU-XrayCIDEr: PPKED 0.351; R2Gen -Helped
Add PoKE to the Base HRNN (ablation)Base HRNN · IU-XrayCIDEr: 0.261 -> 0.285Helped
Add prior medical knowledge (PrMK) (ablation)Base HRNN · IU-XrayCIDEr: 0.261 -> 0.288Helped
Add prior working experience (PrWE) (ablation)Base HRNN · IU-XrayCIDEr: 0.261 -> 0.296Helped
Add both prior medical knowledge and prior working experience (ablation)Base HRNN · IU-XrayCIDEr: 0.261 -> 0.304Helped
Combine PoKE, PrMK, and PrWE (ablation)Base HRNN · IU-XrayCIDEr: 0.261 -> 0.311Helped
Replace LSTM decoder with Transformer Decoder (ablation)PoKE + PrMK + PrWE · IU-XrayCIDEr: 0.311 -> 0.337Helped
Add Adaptive Distilling Attention (ADA) (ablation)Transformer Decoder with PoKE, PrMK, and PrWE · IU-XrayCIDEr: 0.337 -> 0.351Helped
Reverse PoKE order from image-to-topics-to-image to topics-to-image-to-topics (ablation)PoKE · IU-Xrayreport-generation performanceHurt

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