Striking a Balance: Reader Takeaways and Preferences when Integrating Text and Charts

2 August 2022

Papers citing "Striking a Balance: Reader Takeaways and Preferences when Integrating Text and Charts"

7 / 7 papers shown

Title
Navigating the Rashomon Effect: How Personalization Can Help Adjust Interpretable Machine Learning Models to Individual Users Julian Rosenberger Philipp Schröppel Sven Kruschel Mathias Kraus Patrick Zschech Maximilian Förster FAtt 29 0 0 11 May 2025
Visualizationary: Automating Design Feedback for Visualization Designers using LLMs Sungbok Shin Sanghyun Hong Niklas Elmqvist 32 0 0 19 Sep 2024
Same Data, Diverging Perspectives: The Power of Visualizations to Elicit Competing Interpretations Cindy Xiong Bearfield Lisanne Van Weelden Adam Waytz Steven Franconeri 19 8 0 17 Jan 2024
My Model is Unfair, Do People Even Care? Visual Design Affects Trust and Perceived Bias in Machine Learning Aimen Gaba Zhanna Kaufman Jason Chueng Marie Shvakel Kyle Wm. Hall Yuriy Brun Cindy Xiong Bearfield 27 14 0 07 Aug 2023
Chart2Vec: A Universal Embedding of Context-Aware Visualizations Qing Chen Ying Chen Ruishi Zou Wei Shuai Yi Guo Jiazhe Wang Nana Cao 20 3 0 14 Jun 2023
A Qualitative Analysis of Common Practices in Annotations: A Taxonomy and Design Space Md Dilshadur Rahman Ghulam Jilani Quadri Bhavana Doppalapudi D. Szafir Paul Rosen 25 3 0 09 Jun 2023
Communicating Visualizations without Visuals: Investigation of Visualization Alternative Text for People with Visual Impairments C. Jung Shubham Mehta Atharva Kulkarni Yuhang Zhao Yea-Seul Kim 87 55 0 08 Aug 2021