Rixie Tiffany Leong — accepted AI-conference papers

2022

Chart-to-Text: A Large-Scale Benchmark for Chart Summarization

Shankar Kantharaj, Rixie Tiffany Leong, Xiang Lin, Ahmed Masry, Megh Thakkar, Enamul Hoque +1

ACL 2022long

Charts are commonly used for exploring data and communicating insights. Generating natural language summaries from charts can be very helpful for people in inferring key insights that would otherwise require a lot of cognitive and perceptual efforts. We present Chart-to-text, a large-scale benchmark…

Cited by 151 Source ↗PDF ↗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 ↗