Dear Colleagues, Please find below the CFP for our “Visualization Meets AI” workshop, co-located with IEEE PacificVis 2026. We are pleased to announce that this year's workshop is partnering with the Information Visualization journal ( https://journals.sagepub.com/page/ivi/collections) to publish all accepted papers. ===WORKSHOP=== Visualization Meets AI Workshop, colocated with IEEE PacificVis 2026 https://vismeetsai.github.io/ Data visualization requires a thoughtful design process that heavily relies on both domain knowledge and familiarity with visualization techniques. Given the vast design space and inherent complexity, even experts often invest substantial effort to create effective visualizations for exploration or communication. With the rapid advancement of artificial intelligence (AI)—particularly the rise of powerful foundation models such as large language models (LLMs), vision-language models (VLMs), and multimodal AI systems—the field of visualization is undergoing a significant transformation. These cutting-edge models present new opportunities to automate and augment the visualization process. For instance, LLMs can translate natural language queries into visual specifications, assist with data wrangling, and recommend appropriate visualization types. VLMs and multimodal models enable deeper data understanding and interaction by integrating textual, visual, and tabular information, further advancing the creation of intuitive and intelligent visualizations. Concurrently, visualization plays an increasingly vital role in the development and deployment of advanced AI models. As these models grow in complexity and scale, the need for effective visual interfaces and techniques becomes more pressing—to interpret model behavior, debug outputs, and foster transparency, accountability, and human-AI collaboration. This workshop, held in conjunction with IEEE PacificVis 2026, aims to explore this dynamic and rapidly evolving area by fostering communication between the visualization and AI communities. Attendees will engage with the latest research at the intersection of AI-enhanced visualization (AI4VIS) and visualization-enhanced AI (VIS4AI), with a particular focus on how cutting-edge models—such as LLMs, VLMs, and beyond—are reshaping the landscape. ===CALL FOR PAPERS=== We welcome submissions in the form of full papers. All accepted papers will be published in a special issue of the Information Visualization journal. Please check the detailed submission instructions in our website: https://vismeetsai.github.io/ <https://vismeetsai.github.io/> ===IMPORTANT DATES=== - Paper due: December 22, 2025 - 1st cycle notification: January 30, 2026 - Revision due: February 13, 2026 - 2nd cycle notification: February 23, 2026 - Camera-ready with editable source files due: March 2, 2026 - Final notification from the journal’s EIC: March 9, 2026 - Workshop: April 20, 2026 All deadlines are due at 11:59pm Anywhere on Earth (AoE). Thanks, Takanori Fujiwara and Junpeng Wang Visualization Meets AI Workshop Co-Chairs