Jia Qing Tan — accepted AI-conference papers

2022

ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning

Ahmed Masry, Xuan Long Do, Jia Qing Tan, Shafiq Joty, Enamul Hoque

ACL 2022findings

Charts are very popular for analyzing data. When exploring charts, people often ask a variety of complex reasoning questions that involve several logical and arithmetic operations. They also commonly refer to visual features of a chart in their questions. However, most existing datasets do not focus…

Cited by 617 Source ↗PDF ↗code ↗Scholar ↗

2022

OpenCQA: Open-ended Question Answering with Charts

Shankar Kantharaj, Xuan Long Do, Rixie Tiffany Leong, Jia Qing Tan, Enamul Hoque, Shafiq Joty

EMNLP 2022main

Charts are very popular to analyze data and convey important insights. People often analyze visualizations to answer open-ended questions that require explanatory answers. Answering such questions are often difficult and time-consuming as it requires a lot of cognitive and perceptual efforts. To add…

Cited by 50 Source ↗PDF ↗code ↗Scholar ↗