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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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+ - question-answering
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+ - multiple-choice
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+ language:
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+ - en
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+ - zh
9
+ - 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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+
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+
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+ Note: we are reconstructing the dataset again, which will be finihsed before Feb.
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+
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+
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+
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+
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  ## Dataset Structure
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  ### features