DocFusion: A Unified Framework for Document Parsing Tasks

• URL: http://arxiv.org/abs/2412.12505v1
• Date: Tue, 17 Dec 2024 03:20:00 GMT
• Title: DocFusion: A Unified Framework for Document Parsing Tasks
• Authors: Mingxu Chai, Ziyu Shen, Chong Zhang, Yue Zhang, Xiao Wang, Shihan Dou, Jihua Kang, Jiazheng Zhang, Qi Zhang,
• Abstract summary: DocFusion is a lightweight generative model with only 0.28B parameters. It unifies task representations and achieves collaborative training through an improved objective function.
• Score: 22.916911092946897
• License:
• Abstract: Document parsing is essential for analyzing complex document structures and extracting fine-grained information, supporting numerous downstream applications. However, existing methods often require integrating multiple independent models to handle various parsing tasks, leading to high complexity and maintenance overhead. To address this, we propose DocFusion, a lightweight generative model with only 0.28B parameters. It unifies task representations and achieves collaborative training through an improved objective function. Experiments reveal and leverage the mutually beneficial interaction among recognition tasks, and integrating recognition data significantly enhances detection performance. The final results demonstrate that DocFusion achieves state-of-the-art (SOTA) performance across four key tasks.

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