# Modular Multimodal Architecture for Document Classification

arXiv: https://arxiv.org/abs/1912.04376 · HTML: https://mlsanity.com/paper/1912.04376/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Dec 2019.

## Built on by (most cited first, 15 of 15)

- [DocFormer: End-to-End Transformer for Document Understanding](https://mlsanity.com/paper/2106.11539/) (2021)
- [SelfDoc: Self-Supervised Document Representation Learning](https://mlsanity.com/paper/2106.03331/) (2021)
- [LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding](https://mlsanity.com/paper/2202.13669/) (2022)
- [StructuralLM: Structural Pre-training for Form Understanding](https://mlsanity.com/paper/2105.11210/) (2021)
- [Document AI: Benchmarks, Models and Applications](https://mlsanity.com/paper/2111.08609/) (2021)
- [Bi-VLDoc: Bidirectional Vision-Language Modeling for Visually-Rich Document Understanding](https://mlsanity.com/paper/2206.13155/) (2022)
- [Evaluating Out-of-Distribution Performance on Document Image Classifiers](https://mlsanity.com/paper/2210.07448/) (2022)
- [VLCDoC: Vision-Language Contrastive Pre-Training Model for Cross-Modal Document Classification](https://mlsanity.com/paper/2205.12029/) (2022)
- [On Evaluation of Document Classification using RVL-CDIP](https://mlsanity.com/paper/2306.12550/) (2023)
- [EAML: Ensemble Self-Attention-based Mutual Learning Network for Document Image Classification](https://mlsanity.com/paper/2305.06923/) (2023)
- [Context-Aware Classification of Legal Document Pages](https://mlsanity.com/paper/2304.02787/) (2023)
- [Modular Multimodal Machine Learning for Extraction of Theorems and Proofs in Long Scientific Documents (Extended Version)](https://mlsanity.com/paper/2307.09047/) (2023)
- [GlobalDoc: A Cross-Modal Vision-Language Framework for Real-World Document Image Retrieval and Classification](https://mlsanity.com/paper/2309.05756/) (2023)
- [CICA: Content-Injected Contrastive Alignment for Zero-Shot Document Image Classification](https://mlsanity.com/paper/2405.03660/) (2024)
- [ETDPC: A Multimodality Framework for Classifying Pages in Electronic Theses and Dissertations](https://mlsanity.com/paper/2311.04262/) (2023)

## Abstract (arXiv)

Page classification is a crucial component to any document analysis system, allowing for complex branching control flows for different components of a given document. Utilizing both the visual and textual content of a page, the proposed method exceeds the current state-of-the-art performance on the RVL-CDIP benchmark at 93.03% test accuracy.