Survey on Question Answering over Visually Rich Documents: Methods, Challenges, and Trends

Camille Barboule, Benjamin Piwowarski, Yoan Chabot
1/4/2025
cs.CL

No confident code implementation found for this paper.

Abstract

The field of visually-rich document understanding, which involves interacting with visually-rich documents (whether scanned or born-digital), is rapidly evolving and still lacks consensus on several key aspects of the processing pipeline. In this work, we provide a comprehensive overview of state-of-the-art approaches, emphasizing their strengths and limitations, pointing out the main challenges in the field, and proposing promising research directions.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

BoundingDocs: a Unified Dataset for Document Question Answering with Spatial Annotations

82% match2025

VDocRAG: Retrieval-Augmented Generation over Visually-Rich Documents

82% match2 repos852025

Analyzing the Efficacy of an LLM-Only Approach for Image-based Document Question Answering

81% match2023

Towards Complex Document Understanding By Discrete Reasoning

81% match1 repo242022

Visual Question Answering: A Survey on Techniques and Common Trends in Recent Literature

81% match2023

PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answering

80% match2024

Cite this paper

@article{barboule2025survey,
  title  = {Survey on Question Answering over Visually Rich Documents: Methods, Challenges, and Trends},
  author = {Camille Barboule and Benjamin Piwowarski and Yoan Chabot},
  year   = {2025},
  eprint = {2501.02235},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2501.02235v2}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2501.02235.svg)](https://codeofpaper.com/paper/2501.02235)

Discussion