Financial Multimodal Mathematical Reasoning QA Dataset💰

Dataset Description

FinQA is a dataset for financial reasoning and question answering. It contains questions, financial background information, and corresponding answers. The dataset includes text and visual data, with the visual data represented by images in a JSON file.

Dataset Structure

The dataset contains the following fields:

• ID: Unique identifier for each question.
• Share Context: Background information related to the question.
• Share Image: Path to the associated visual data.
• Question Text: The question to be answered.
• Options: Multiple‑choice options.
• Answer: Correct answer.
• Explanation: Detailed explanation of the answer.

Annotation Process

Annotations are performed by financial experts to ensure high accuracy and consistency.

Bias, Risks, and Limitations

The dataset may contain inherent biases originating from its source financial documents. Users should be cautious when generalizing results.

Recommendations

Avoid over‑generalization of model outputs and consider domain‑specific adaptation.

Citation

BibTeX:

@article{article_id,
title     = {Enhancing Multimodal Financial Math Reasoning with Reflection Module and Error Log},
author    = {Shuangyan Deng, Haizhou Peng, ChunHou Liu, Jiachen Xu},
year      = {2024},
journal   = {arXiv},
primaryClass={cs.CV}
}

Dataset Card Authors

[The University of Auckland]

Dataset Card Contact

[hpen397@aucklanduni.ac.nz]