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README.md
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---
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license: apache-2.0
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task_categories:
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- question-answering
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- multiple-choice
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language:
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- en
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- zh
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- fr
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tags:
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- finance
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pretty_name: >-
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FAMMA: A Benchmark for Financial Domain Multilingual Multimodal Question
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Answering
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size_categories:
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- 1K<n<10K
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---
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## Introduction
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FAMMA dataset consists of 1,758 meticulously collected multimodal questions. The questions encompass three heterogeneous image types - tables, charts and text & math screenshots - and span eight subfields in finance, comprehensively covering topics across major asset classes. Additionally, all the questions are categorized by three difficulty levels — easy, medium, and hard - and are available in three languages — English, Chinese, and French. Furthermore, the questions are divided into two types: multiple-choice and open questions.
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The leaderboard is regularly updated and can be accessed at https://famma-bench.github.io/famma/.
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## Dataset Structure
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### features
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---
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license: apache-2.0
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+
task_categories:
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4 |
+
- question-answering
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5 |
+
- multiple-choice
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6 |
+
language:
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+
- en
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+
- zh
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+
- fr
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+
tags:
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+
- finance
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+
pretty_name: >-
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+
FAMMA: A Benchmark for Financial Domain Multilingual Multimodal Question
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14 |
+
Answering
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+
size_categories:
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+
- 1K<n<10K
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17 |
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---
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## Introduction
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FAMMA dataset consists of 1,758 meticulously collected multimodal questions. The questions encompass three heterogeneous image types - tables, charts and text & math screenshots - and span eight subfields in finance, comprehensively covering topics across major asset classes. Additionally, all the questions are categorized by three difficulty levels — easy, medium, and hard - and are available in three languages — English, Chinese, and French. Furthermore, the questions are divided into two types: multiple-choice and open questions.
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The leaderboard is regularly updated and can be accessed at https://famma-bench.github.io/famma/.
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Note: we are reconstructing the dataset again, which will be finihsed before Feb.
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## Dataset Structure
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### features
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