The paper discusses the use of Large Language Models (LLMs) in generating visualizations, noting both their potential and the challenges they present. It introduces EvaLLM, a theoretical evaluation stack designed…
Continue readingThis paper explores how counterfactual visualizations, which present what might have been true under different circumstances, can aid in understanding data. The authors propose a model of causality comprehension, linking…
Continue readingAs new data collection methods become increasingly common, traditional techniques for data visualization and dimension reduction are becoming less adequate. This article proposes a surrogate-assisted sufficient dimension reduction (SDR) method…
Continue readingThe article delves into the role of casual data visualizations in communicating data to the general public. It focuses on how practitioners make design decisions based on their target audiences…
Continue readingThis article introduces HPC2lusterScape, a visualization system designed to enhance the efficiency and transparency of shared high-performance computing (HPC) clusters used for large-scale AI models. The system provides a comprehensive…
Continue readingThe research paper delves into a comprehensive analysis of the workplace, employing data science methodologies and visualization techniques. It focuses on key facets like employee satisfaction, engagement levels, work environment…
Continue readingThis article presents ‘Vistrust’, a multidimensional framework for understanding trust in data visualizations. The authors argue that trust is crucial in interpreting and making decisions based on visualizations. They propose…
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