Research map / Image generation / Text-to-image diffusion
Phrase-Based Presentation Slides Generation for Academic Papers
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use phrase-based selection and alignment instead of sentence extraction (PPSGen) | slide generation · Table 1 metric-A | ROUGE-1: 0.14 -> 0.26 | Helped |
| use phrase-based selection instead of PPSGen | slide generation · Table 1 metric-C | ROUGE-2: 0.043 -> 0.117 | Helped |
| Relation-First greedy algorithm instead of Saliency-First (ablation) | phrase-based slides generation · Table 1 metric-A | ROUGE-1: 0.25 -> 0.26 | Helped |
| Relation-First instead of Saliency-First, ignoring L1/L2 distinction (ablation) | phrase-based slides generation · Table 2 | ROUGE-2: 0.114 -> 0.117 | Helped |
| evaluate without differentiating L1 and L2 bullets | phrase-based approach vs baselines · Table 2 | ROUGE-1: 0.30 vs 0.17 (best baseline) | Helped |
Closest papers by meaning
- Towards Topic-Aware Slide Generation For Academic Papers With Unsupervised Mutual Learning (AAAI 2021 · similarity 0.90)
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- Paper2Poster: Towards Multimodal Poster Automation from Scientific Papers (NeurIPS 2025 · similarity 0.81)
- Language Models of Code Are Few-Shot Planners and Reasoners for Multi-Document Summarization with Attribution (AAAI 2025 · similarity 0.80)
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