PaperX: A Unified Framework for Multimodal Academic Presentation Generation with Scholar DAG
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2026
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866908827284144128 |
|---|---|
| author | Yu, Tao Zhang, Minghui Cui, Zhiqing Wang, Hao Luo, Zhongtian Chai, Shenghua Gong, Junhao Peng, Yuzhao Zhou, Yuxuan Yang, Yujia Zhang, Zhenghao Jin, Haopeng Wang, Xinming Xiong, Yufei Yang, Jiabing Yuan, Jiahao Wang, Hanqing Yi, Hongzhu Huang, Yan Wang, Liang |
| author_facet | Yu, Tao Zhang, Minghui Cui, Zhiqing Wang, Hao Luo, Zhongtian Chai, Shenghua Gong, Junhao Peng, Yuzhao Zhou, Yuxuan Yang, Yujia Zhang, Zhenghao Jin, Haopeng Wang, Xinming Xiong, Yufei Yang, Jiabing Yuan, Jiahao Wang, Hanqing Yi, Hongzhu Huang, Yan Wang, Liang |
| contents | Transforming scientific papers into multimodal presentation content is essential for research dissemination but remains labor intensive. Existing automated solutions typically treat each format as an isolated downstream task, leading to redundant processing and semantic inconsistency. We introduce PaperX, a unified framework that models academic presentation generation as a structural transformation and rendering process. Central to our approach is the Scholar DAG, an intermediate representation that decouples the paper's logical structure from its final presentation syntax. By applying adaptive graph traversal strategies, PaperX generates diverse, high quality outputs from a single source. Comprehensive evaluations demonstrate that our framework achieves the state of the art performance in content fidelity and aesthetic quality while significantly improving cost efficiency compared to specialized single task agents. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_03866 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | PaperX: A Unified Framework for Multimodal Academic Presentation Generation with Scholar DAG Yu, Tao Zhang, Minghui Cui, Zhiqing Wang, Hao Luo, Zhongtian Chai, Shenghua Gong, Junhao Peng, Yuzhao Zhou, Yuxuan Yang, Yujia Zhang, Zhenghao Jin, Haopeng Wang, Xinming Xiong, Yufei Yang, Jiabing Yuan, Jiahao Wang, Hanqing Yi, Hongzhu Huang, Yan Wang, Liang Digital Libraries Artificial Intelligence Transforming scientific papers into multimodal presentation content is essential for research dissemination but remains labor intensive. Existing automated solutions typically treat each format as an isolated downstream task, leading to redundant processing and semantic inconsistency. We introduce PaperX, a unified framework that models academic presentation generation as a structural transformation and rendering process. Central to our approach is the Scholar DAG, an intermediate representation that decouples the paper's logical structure from its final presentation syntax. By applying adaptive graph traversal strategies, PaperX generates diverse, high quality outputs from a single source. Comprehensive evaluations demonstrate that our framework achieves the state of the art performance in content fidelity and aesthetic quality while significantly improving cost efficiency compared to specialized single task agents. |
| title | PaperX: A Unified Framework for Multimodal Academic Presentation Generation with Scholar DAG |
| topic | Digital Libraries Artificial Intelligence |
| url | https://arxiv.org/abs/2602.03866 |