# Intelligent Canvas: Enabling Design-Like Exploratory Visual Data Analysis with Generative AI through Rapid Prototyping, Iteration and Curation

arXiv: https://arxiv.org/abs/2402.08812 · HTML: https://mlsanity.com/paper/2402.08812/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 40 references that are in the map.
- First posted on arXiv 13 Feb 2024.

## Builds on (most cited first, 8 of 8)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Evaluating Large Language Models Trained on Code](https://mlsanity.com/paper/2107.03374/) (2021)
- [StickyLand: Breaking the Linear Presentation of Computational Notebooks](https://mlsanity.com/paper/2202.11086/) (2022)
- [Boba: Authoring and Visualizing Multiverse Analyses](https://mlsanity.com/paper/2007.05551/) (2020)
- [Lyra 2: Designing Interactive Visualizations by Demonstration](https://mlsanity.com/paper/2008.09576/) (2020)
- [Understanding and Supporting Debugging Workflows in Multiverse Analysis](https://mlsanity.com/paper/2210.03804/) (2022)
- [Freeform Templates: Combining Freeform Curation with Structured Templates](https://mlsanity.com/paper/2305.00937/) (2023)
- [WHATSNEXT: Guidance-enriched Exploratory Data Analysis with Interactive, Low-Code Notebooks](https://mlsanity.com/paper/2308.09802/) (2023)

## Built on by (most cited first, 2 of 2)

- ["The Diagram is like Guardrails": Structuring GenAI-assisted Hypotheses Exploration with an Interactive Shared Representation](https://mlsanity.com/paper/2503.16791/) (2025)
- [AdaLens: Interactive Storyline for Monitoring and Steering Long-Running Agentic Data Analysis](https://mlsanity.com/paper/2608.17834/) (2026)

## Abstract (arXiv)

Complex data analysis inherently seeks unexpected insights through exploratory visual analysis methods, transcending logical, step-by-step processing. However, existing interfaces such as notebooks and dashboards have limitations in exploration and comparison for visual data analysis. Addressing these limitations, we introduce a "design-like" intelligent canvas environment integrating generative AI into data analysis, offering rapid prototyping, iteration, and comparative visualization management. Our dual contributions include the integration of generative AI components into a canvas interface, and empirical findings from a user study (N=10) evaluating the effectiveness of the canvas interface.