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[ChartVE](https://huggingface.co/khhuang/chartve) (Chart Visual Entailment) is a visual entailment model introduced in the paper "Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning" for evaluating the factuality of a generated caption sentence with regard to the input chart. The model takes in a chart figure and a caption sentence as input, and outputs an entailment probability. This repository hosts the training and validation data for ChartVE.
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## Paper Information
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[ChartVE](https://huggingface.co/khhuang/chartve) (Chart Visual Entailment) is a visual entailment model introduced in the paper "Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning" for evaluating the factuality of a generated caption sentence with regard to the input chart. The model takes in a chart figure and a caption sentence as input, and outputs an entailment probability. This repository hosts the training and validation data for ChartVE.
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### Fields
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Below, we illustrate the fields in each instance.
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- `image`: The path to chart image. Images can be found in [image.zip](https://huggingface.co/datasets/khhuang/chartve_dataset/blob/main/images.zip).
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- `sentence`: The sentence used as the _hypothesis_.
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- `label`: An indicator about whether the chart entails the given `sentence`.
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- `manipulation_type`: The type of perturbation that alters the original sentence (this is only applicable for non-entailment instances).
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- `dataset`: The source dataset of the chart `image`.
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## Paper Information
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