| license: cc-by-nc-4.0 | |
| <h1 align="center"> | |
| PaDoc: Layout-Grounded Parallel Decoding for Document Parsing | |
| </h1> | |
| <p align="center"> | |
| <a href="https://github.com/Longin-Yu/Padoc"><img src="https://img.shields.io/badge/GitHub-PaDoc-181717.svg?logo=github" alt="GitHub"></a> | |
| <a href="https://arxiv.org/abs/2608.06146"><img src="https://img.shields.io/badge/arXiv-2608.06146-b31b1b.svg" alt="arXiv"></a> | |
| <a href="https://huggingface.co/Longin-Yu/PaDoc"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-yellow" alt="Hugging Face"></a> | |
| </p> | |
|  | |
| PaDoc is an open-source implementation of tree-supervised training and | |
| fork-token decoding for document parsing. A single image-text model emits a | |
| compact main sequence and starts independent content branches at learned fork | |
| tokens. No draft model or additional prediction head is required. | |
| For more details, refer to our github repo. |