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  ## Dataset Description
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- We introduce **EMMA (Enhanced MultiModal reAsoning)**, a benchmark targeting organic multimodal reasoning across mathematics, physics, chemistry, and coding.
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  EMMA tasks demand advanced cross-modal reasoning that cannot be solved by thinking separately in each modality, offering an enhanced test suite for MLLMs' reasoning capabilities.
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  EMMA is composed of 2,788 problems, of which 1,796 are newly constructed, across four domains. Within each subject, we further provide fine-grained labels for each question based on the specific skills it measures.
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  - Code: https://github.com/hychaochao/EMMA
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  - Project: https://emma-benchmark.github.io/
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- ## Dataset Usage
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- ### Data Downloading
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- You can download the dataset by the following command (Taking downloading math data as an example):
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- ```python
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- from datasets import load_dataset
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- dataset = load_dataset("luckychao/EMMA", "Math", split="test")
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- ```
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  ### Data Format
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  }
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  ```
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- ### Automatic Evaluation
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- To automatically evaluate a model on the dataset, please refer to our GitHub repository [here](https://github.com/hychaochao/EMMA).
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  ## Citation
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  ```
 
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  ## Dataset Description
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+ **EMMA (Enhanced MultiModal reAsoning)** is a benchmark targeting organic multimodal reasoning across mathematics, physics, chemistry, and coding.
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  EMMA tasks demand advanced cross-modal reasoning that cannot be solved by thinking separately in each modality, offering an enhanced test suite for MLLMs' reasoning capabilities.
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  EMMA is composed of 2,788 problems, of which 1,796 are newly constructed, across four domains. Within each subject, we further provide fine-grained labels for each question based on the specific skills it measures.
 
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  - Code: https://github.com/hychaochao/EMMA
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  - Project: https://emma-benchmark.github.io/
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  ### Data Format
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  }
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  ```
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  ## Citation
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  ```