README.md

metadata

title: PaDoc Document Parser
emoji: 📄
colorFrom: indigo
colorTo: pink
sdk: gradio
sdk_version: 6.22.0
app_file: app.py
short_description: Parse document layout regions and content with PaDoc
python_version: '3.12'
startup_duration_timeout: 1h

PaDoc: Layout-Grounded Parallel Decoding for Document Parsing

This Space demonstrates PaDoc, an end-to-end document parser that leverages parallel decoding. A single image-text model emits a compact main sequence of layout boxes and starts independent content branches at learned fork tokens — no draft model or additional prediction head is required.

How it works

1. Upload a document image (or try one of the examples).
2. Click Parse document — the model predicts layout bounding boxes in [0, 1000] coordinates and decodes a content branch for each region.
3. The annotated image shows detected regions; the markdown output lists each region's category and extracted text.

Execution modes

• Sequential (default): batch=1 reference decoding — finishes each branch before resuming the main stream.
• Parallel: prefills the prompt once, snapshots the parent KV cache at each fork, and advances the main stream plus all active branches together in one lockstep GPU batch.

Model

• Model: Longin-Yu/PaDoc (Qwen3-VL 2B base)
• Paper: arXiv:2608.06146
• Code: GitHub

License

Model weights are under CC-BY-NC-4.0. Example document images are generated for this demo.