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README.md
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ChartVE is a visual entailment model introduced in the paper "Do LVLMs Understand Charts?
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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. To compute the the entailment probability, please refer to the "How to use" section below. The underlying architecture of this model is UniChart.
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### How to use
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ChartVE is a visual entailment model introduced in the paper "Do LVLMs Understand Charts?
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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. To compute the the entailment probability, please refer to the "How to use" section below. The underlying architecture of this model is UniChart.
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Note that this model expects a caption sentence as textual inputs. For captions that are longer than one sentences, one should split the caption into multiple sentences, feed individual sentences to ChartVE, and then aggregate the scores. Below, we provide an example of how to use ChartVE.
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### How to use
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