arXiv:2609.08657v1 Announce Type: cross
Abstract: Charts are structured visual compositions whose elements have distinct functional roles, semantic correspondences, and visibility relations. This str...
By Xiaochuan Zhong, Yifan Hou, Chenxi Pang, Shaobo Cui
arXiv:2510.17932v5 Announce Type: replace-cross
Abstract: We introduce Chart2Code, a new benchmark for evaluating the chart understanding and code generation capabilities of large multimodal models (...
By Jiahao Tang, Henry Hengyuan Zhao, Lijian Wu, Zijian Zhang, Yifei Tao, Dongxing Mao, Yang Wan, Jingru Tan, Min Zeng, Min Li, Alex Jinpeng Wang
Vision-language models (VLMs) have shown strong capabilities in generating visualization code from textual or visual specifications. However, real-world visualization authoring is inherently iterative: users frequently revise existing visualizations to repair flawed charts or adapt them to desired styles.
arXiv:2609.26208v1 Announce Type: new
Abstract: Data visualization is central to analytical reasoning, but real-world analysis increasingly requires language-driven interactive interfaces rather than...
By Mizanur Rahman, Aaryaman Kartha, Enamul Hoque Prince
ChartRevise is a new dataset and evaluation protocol designed for exact chart editing via code. It contains 92,438 records covering 344 edit types across 20 chart types and three plotting libraries, built using the grammar of graphics and source‑program checks to ensure applicability. The protocol measures atomic requirement completion, detects gratuitous changes and missed coupled updates, and combines these with execution and rendering success to determine exact‑edit success.
By Jiaxiang Tang, Yi Zhou, Chad DeLuca, Rogerio Feris, Ahmed Khalil Omran, Zhi-Li Zhang, Pengyuan Li, Ali Anwar
arXiv:2510. 04514v3 Announce Type: replace Abstract: Recent multimodal LLMs have shown promise in chart-based visual question answering, but their performance declines sharply on unannotated charts-those requiring precise visual interpretation rather than relying on textual shortcuts.
By Rachneet Kaur, Nishan Srishankar, Zhen Zeng, Sumitra Ganesh, Manuela Veloso