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

Source: [Survey on Question Answering over Visually Rich Documents: Methods, Challenges, and Trends](<https://www.sota2.com/research/paper/68fa775d1e209131cea72bdb>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T04:16:49.987Z

Authors: Camille Barboule, Benjamin Piwowarski, Yoan Chabot

Published: 2025-01-04T08:45:24.000Z

## 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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2501.02235>)

[PDF](<https://arxiv.org/pdf/2501.02235.pdf>)