[2510.22373] VisJudge-Bench: Aesthetics and Quality Assessment of Visualizations

Computer Science > Computation and Language arXiv:2510.22373 (cs) [Submitted on 25 Oct 2025 (v1), last revised 2 Mar 2026 (this version, v3)] Title:VisJudge-Bench: Aesthetics and Quality Assessment of Visualizations Authors:Yupeng Xie, Zhiyang Zhang, Yifan Wu, Sirong Lu, Jiayi Zhang, Zhaoyang Yu, Jinlin Wang, Sirui Hong, Bang Liu, Chenglin Wu, Yuyu Luo View a PDF of the paper titled VisJudge-Bench: Aesthetics and Quality Assessment of Visualizations, by Yupeng Xie and 10 other authors View PDF HTML (experimental) Abstract:Visualization, a domain-specific yet widely used form of imagery, is an effective way to turn complex datasets into intuitive insights, and its value depends on whether data are faithfully represented, clearly communicated, and aesthetically designed. However, evaluating visualization quality is challenging: unlike natural images, it requires simultaneous judgment across data encoding accuracy, information expressiveness, and visual aesthetics. Although multimodal large language models (MLLMs) have shown promising performance in aesthetic assessment of natural images, no systematic benchmark exists for measuring their capabilities in evaluating visualizations. To address this, we propose VisJudge-Bench, the first comprehensive benchmark for evaluating MLLMs' performance in assessing visualization aesthetics and quality. It contains 3,090 expert-annotated samples from real-world scenarios, covering single visualizations, multiple visualizations, and dashbo...