Papers by Jia Qing Tan

2 papers
ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning (2022.findings-acl)

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Challenge: Existing datasets that focus on complex reasoning questions do not address such questions as they are template-based and answers come from a fixed-vocabulary.
Approach: They propose a large-scale benchmark that uses visual and logical reasoning to answer questions using a transformer-based model.
Outcome: The proposed models achieve state-of-the-art on the previous datasets and on the current one, but also show that they have several challenges in answering complex reasoning questions.
OpenCQA: Open-ended Question Answering with Charts (2022.emnlp-main)

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Challenge: OpenCQA is a task to answer open-ended questions about charts with descriptive texts.
Approach: They propose a task to answer open-ended questions about charts with descriptive texts.
Outcome: The proposed task is to answer an open-ended question about a chart with descriptive texts.

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