DV-World: Benchmarking Data Visualization Agents in Real-World Scenarios
From Daily Paper Cast by Jingwen Liang, Gengyu Wang
April 30, 2026 · 23 min · Episode 1817
About this episode
This episode discusses DV-World, a benchmark for evaluating data visualization agents in real-world scenarios.
🤗 Upvotes: 37 | cs.CL Authors: Jinxiang Meng, Shaoping Huang, Fangyu Lei, Jingyu Guo, Haoxiang Liu, Jiahao Su, Sihan Wang, Yao Wang, Enrui Wang, Ye Yang, Hongze Chai, Jinming Lv, Anbang Yu, Huangjing Zhang, Yitong Zhang, Yiming Huang, Zeyao Ma, Shizhu He, Jun Zhao, Kang Liu Title: DV-World: Benchmarking Data Visualization Agents in Real-World Scenarios Arxiv: http://arxiv.org/abs/2604.25914v1 Abstract: Real-world data visualization (DV) requires native environmental grounding, cross-platform evolution, and proactive intent alignment. Yet, existing benchmarks often suffer from code-sandbox confinement, single-language creation-only tasks, and assumption of perfect intent. To bridge these gaps, we introduce DV-World, a benchmark of 260 tasks designed to evaluate DV agents across real-world professional lifecycles. DV-World spans three domains: DV-Sheet for native spreadsheet manipulation including chart and dashboard creation as well as diagnostic repair; DV-Evolution for adapting and restructuring reference visual artifacts to fit new data across diverse programming paradigms and DV-Interact for proactive intent alignment with a user simulator that mimics real-world ambiguous…
Topics covered
- data visualization
- benchmarking
- real-world scenarios
- machine learning
- evaluation frameworks
Keywords
- DV-World
- data visualization agents
- benchmarking
- real-world data
- evaluation framework
- machine learning
- cross-platform
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