3MVRD: Multimodal Multi-task Multi-teacher Visually-Rich Form Document Understanding
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Abstract (arXiv)
This paper presents a groundbreaking multimodal, multi-task, multi-teacher joint-grained knowledge distillation model for visually-rich form document understanding. The model is designed to leverage insights from both fine-grained and coarse-grained levels by facilitating a nuanced correlation between token and entity representations, addressing the complexities inherent in form documents. Additionally, we introduce new inter-grained and cross-grained loss functions to further refine diverse multi-teacher knowledge distillation transfer process, presenting distribution gaps and a harmonised understanding of form documents. Through a comprehensive evaluation across publicly available form document understanding datasets, our proposed model consistently outperforms existing baselines, showcasing its efficacy in handling the intricate structures and content of visually complex form documents.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 16 of its 21 references that are in the map. First posted on arXiv 28 Feb 2024.
Builds on
16 of 21 references.
References · 16
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- 2023FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extractioncited by 20
4 more
- 2019Visual Question Answering using Deep Learning: A Survey and Performance Analysiscited by 19
- 2022V-Doc : Visual questions answers with Documentscited by 19
- 2022Doc-GCN: Heterogeneous Graph Convolutional Networks for Document Layout Analysiscited by 17
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Citing papers per year: 2024: 2; 2025: 0; 2026: 1.
3 papers.
- 2024Deep Learning based Visually Rich Document Content Understanding: A Surveycited by 21
- 2024SynJAC: Synthetic-data-driven Joint-granular Adaptation and Calibration for Domain Specific Scanned Document Key Information Extractioncited by 4
- 2026LAVA: Logic-Aware Validation and Augmentation Framework for Large-Scale Financial Document Auditingcited by 0
- 2026LAVA: Logic-Aware Validation and Augmentation Framework for Large-Scale Financial Document Auditing17 Aug 2026
- 2024SynJAC: Synthetic-data-driven Joint-granular Adaptation and Calibration for Domain Specific Scanned Document Key Information Extraction2 Oct 2024
- 2024Deep Learning based Visually Rich Document Content Understanding: A Survey2 Aug 2024