OpenAI Blog
Hex turns complex analysis into visual reports with GPT‑6 Astra
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arXiv AI
Oct 23
Charts as Epistemic Actions for Experience-Driven Agentic Data Analysis
arXiv:2610. 30072v1 Announce Type: new Abstract: Data agents built on ReAct-style loops now execute complex analytical workflows over structured data, yet their intermediate reasoning still runs almost entirely through text.
Microsoft Research
Oct 22
Flint-interactive: A language for creating interactive data visualizations
Flint‑interactive is a language developed by Microsoft Research that enables AI agents to generate interactive data visualizations. It allows users to click on charts, filter data, highlight related content, and explore beyond the initially chosen view. The system is designed to enhance user interaction with visual data representations.
Microsoft Research
Jul 8
Flint: A visualization language for the AI era
Short chart specifications are easy to write, but often produce uninspiring results. Flint is an open-source visualization language that offers a middle path, letting AI agents create expressive charts from compact, human-editable specifications.
arXiv AI
Jun 26
HiLSVA: Design and Evaluation of a Human-in-the-Loop Agentic System for Scientific Visualization
arXiv:2606. 26614v1 Announce Type: cross Abstract: Large language model (LLM) agents enable natural language interaction for scientific visualization (SciVis).
arXiv AI
Jun 6
SciVisAgentSkills: Design and Evaluation of Agent Skills for Scientific Data Analysis and Visualization
arXiv:2606. 05525v1 Announce Type: new Abstract: Recent advances in agentic visualization have enabled the translation of natural language into executable scientific visualization (SciVis) workflows.
arXiv AI
Oct 19
ATWL: A Formal Language for Representing, Comparing, and Reusing Visual Analytics Workflows
The paper introduces ATWL, a declarative language that formalizes visual analytics workflows by specifying typed artifacts and transforms with defined analytical intents and actors. A library of 54 workflows, curated from published papers with LLM assistance, demonstrates patterns such as human-machine labor division and refinement cycles. Experiments show that using ATWL and the library improves LLM-designed workflows, though branching remains a limitation requiring syntax extension.