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DOC2PPT: Automatic Presentation Slides Generation from Scientific Documents

AAAI 2022 · Vision-language and multimodal › Human and embodied modeling · approach: Layout-aware document understanding · 36 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace the flat progress tracker with hierarchical section-slide-object tracking (ablation)DOC2PPT · DOC2PPT test setstructural LCS: 51.72% -> 64.15%Helped
Add the paraphrasing loss (ablation)Hierarchical PT without PAR, with TIM · DOC2PPT test setROUGE-SL: 26.52 -> 29.40Helped
Add the paraphrasing loss (ablation)Hierarchical PT without PAR or TIM · DOC2PPT test setTFR: 8.58 -> 9.23Helped
Add the text-figure matching loss (ablation)Hierarchical PT without PAR · DOC2PPT test setLC-FS F1: 20.99 -> 24.36Helped
Add the text-figure matching loss (ablation)Hierarchical PT without PAR · DOC2PPT test setLC-FS recall: 26.26 -> 25.31Hurt
Add the text-figure matching loss (ablation)Hierarchical PT without PAR · DOC2PPT test setROUGE-SL: 24.93 -> 26.52Helped
Enable figure post-processing to remove low-relevance figures and add high-relevance ones (ablation)Hierarchical PT with PAR and TIM · DOC2PPT test setLC-FS F1: 24.36 -> 31.26Helped
Enable figure post-processing to remove low-relevance figures and add high-relevance ones (ablation)Hierarchical PT with PAR and TIM · DOC2PPT test setTFR: 11.82 -> 17.49Helped
Use learned layout prediction instead of template-based layout (ablation)DOC2PPT · DOC2PPT test setmIoU: 42.96 -> 50.82Helped
Condition the paraphraser on the object state (ablation)DOC2PPT paraphraser · DOC2PPT test setROUGE-L: 31.95 -> 32.27Helped

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