ChartSumm: A Comprehensive Benchmark for Automatic Chart Summarization of Long and Short Summaries

Automatic chart to text summarization is an effective tool for the visually impaired people along with providing precise insights of tabular data in natural language to the user. A large and well-structured dataset is always a key part for data driven models. In this paper, we propose ChartSumm: a large-scale benchmark dataset consisting of a total of 84,363 charts along with their metadata and descriptions covering a wide range of topics and chart types to generate short and long summaries. Extensive experiments with strong baseline models show that even though these models generate fluent and informative summaries by achieving decent scores in various automatic evaluation metrics, they often face issues like suffering from hallucination, missing out important data points, in addition to incorrect explanation of complex trends in the charts. We also investigated the potential of expanding ChartSumm to other languages using automated translation tools. These make our dataset a challenging benchmark for future research.Comment: Accepted as a long paper at the Canadian AI 202

A simple design of a Matlab-Based function for topographical presentation of FNIRS Data

Functional Near-Infrared Spectroscopy (fNIRS) has aggrandized the domain of Neurophotonics and Imaging research to reach its apex. With enhanced spatial resolution with the pre-existing temporal resolution, fNIRS can be more promising for the functional analysis of the brain. Hardware integrated software for fNIRS analysis is affluent as well as limited for users. The analysis based on MATLAB is done with the Graphical User Interface (GUI) that are difficult to use because they involve numerous steps, coefficients, and related files. This is a simple MATLAB-based study that includes the generation of the brain activation patterns based on oxygenation and de-oxygenation of hemoglobin and enhancing spatial resolution for the better identification of brain functionality. Brain activation pattern based on the recorded fNIRS data is created in the form of a color-coded map. The map is registered to the brain surface image which provides better visuality of the activation scheme of the brain with an anatomical view. This research intends to encourage prolific researchers in this research area to conduct simplified and cost-effective analyses of the fNIRS study