ChartThinker: A Contextual Chain-of-Thought Approach to Optimized Chart Summarization

arXiv:2403.11236v1 Announce Type: new
Abstract: Data visualization serves as a critical means for presenting data and mining its valuable insights. The task of chart summarization, through natural language processing techniques, facilitates in-depth data analysis of charts. However, there still are notable deficiencies in terms of visual-language matching and reasoning ability for existing approaches. To address these limitations, this study constructs a large-scale dataset of comprehensive chart-caption pairs and fine-tuning instructions on each chart. Thanks to the broad coverage of various …

abstract analysis arxiv charts cs.cl data data analysis data visualization however insights language language processing mining natural natural language natural language processing presenting processing reasoning summarization terms thought through type visual visualization