# PlotEdit: Natural Language-Driven Accessible Chart Editing in PDFs via Multimodal LLM Agents

arXiv: https://arxiv.org/abs/2501.11233 · HTML: https://mlsanity.com/paper/2501.11233/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 10 references that are in the map.
- First posted on arXiv 20 Jan 2025.

## Builds on (most cited first, 5 of 5)

- [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://mlsanity.com/paper/2201.11903/) (2022)
- [ChartLlama: A Multimodal LLM for Chart Understanding and Generation](https://mlsanity.com/paper/2311.16483/) (2023)
- [DePlot: One-shot visual language reasoning by plot-to-table translation](https://mlsanity.com/paper/2212.10505/) (2022)
- [NL4DV: A Toolkit for Generating Analytic Specifications for Data Visualization from Natural Language Queries](https://mlsanity.com/paper/2008.10723/) (2020)
- [ChartReformer: Natural Language-Driven Chart Image Editing](https://mlsanity.com/paper/2403.00209/) (2024)

## Built on by (most cited first, 3 of 3)

- [ChartE3: A Comprehensive Benchmark for End-to-End Chart Editing](https://mlsanity.com/paper/2601.21694/) (2026)
- [Does It Run and Is That Enough? Revisiting Text-to-Chart Generation with a Multi-Agent Approach](https://mlsanity.com/paper/2506.06175/) (2025)
- [ChartRevise: A Dataset and Evaluation Protocol for Exact Chart Editing via Code](https://mlsanity.com/paper/2609.38642/) (2026)

## Abstract (arXiv)

Chart visualizations, while essential for data interpretation and communication, are predominantly accessible only as images in PDFs, lacking source data tables and stylistic information. To enable effective editing of charts in PDFs or digital scans, we present PlotEdit, a novel multi-agent framework for natural language-driven end-to-end chart image editing via self-reflective LLM agents. PlotEdit orchestrates five LLM agents: (1) Chart2Table for data table extraction, (2) Chart2Vision for style attribute identification, (3) Chart2Code for retrieving rendering code, (4) Instruction Decomposition Agent for parsing user requests into executable steps, and (5) Multimodal Editing Agent for implementing nuanced chart component modifications - all coordinated through multimodal feedback to maintain visual fidelity. PlotEdit outperforms existing baselines on the ChartCraft dataset across style, layout, format, and data-centric edits, enhancing accessibility for visually challenged users and improving novice productivity.