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Chart Question Answering Conclusive Consequent Certain

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chart question answering. Chart question answering is a type of natural language processing (nlp) that combines computer vision and machine learning to allow. In this survey, we systematically review the current state‐of‐the‐art research focusing on the problem of chart question answering.

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chart question answering In this survey, we systematically review the current state‐of‐the‐art research focusing on the problem of chart question answering. Chart question answering (cqa) systems typically take a chart and a natural language question as input and automatically. To address the unique challenges in our benchmark involving visual and logical reasoning over charts, we present two.

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We Provide A Taxonomy By Identifying Several Important Dimensions.

In this survey, we systematically review the current state‐of‐the‐art research focusing on the problem of chart question answering. Chart question answering is a type of natural language processing (nlp) that combines computer vision and machine learning to allow. Chart question answering (cqa) systems typically take a chart and a natural language question as input and automatically.

To Address The Unique Challenges In Our Benchmark Involving Visual And Logical Reasoning Over Charts, We Present Two.

Chart question answering (cqa) is a newly proposed visual question answering (vqa) task where an algorithm must answer questions. A benchmark for question answering about charts with visual and logical reasoning Based on the structured text data, a large language model (llm) is employed to answer the given questions to achieve chart.