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Dismiss alert {{ message }} rickyang1114 / multimodal-deepresearcher Public Notifications You must be signed in to change notification settings Fork 3 Star 57 Code Issues 1 Pull requests 0 Actions Projects Security and quality 0 Insights Additional navigation options Code Issues Pull requests Actions Projects Security and quality Insights rickyang1114/multimodal-deepresearcher main Branches Tags Go to file Code Open more actions menu Folders and files Name Name Last commit message Last commit date Latest commit History 52 Commits 52 Commits .devcontainer .devcontainer .github .github .husky .husky .vscode .vscode .yarn/ releases .yarn/ releases app app components components css css data data faq faq layouts layouts public public scripts scripts src src .env.example .env.example .gitattributes .gitattributes .gitignore .gitignore .yarnrc.yml .yarnrc.yml LICENSE LICENSE README-tailwind-started-blog.md README-tailwind-started-blog.md README.md README.md contentlayer.config.ts contentlayer.config.ts eslint.config.mjs eslint.config.mjs jsconfig.json jsconfig.json next-env.d.ts next-env.d.ts next.config.js next.config.js package.json package.json postcss.config.js postcss.config.js prettier.config.js prettier.config.js tsconfig.json tsconfig.json yarn.lock yarn.lock View all files Repository files navigation README MIT license More items Multimodal DeepResearcher: Generating Text-Chart Interleaved Reports From Scratch with Agentic Framework We introduce an agentic framework that automatically generates comprehensive multimodal reports from scratch with interleaved texts and visualizations , going beyond text-only content generation. The paper has been accepted as an oral presentation at AAAI 2026. This repo contains the source code for the project's demo website and some utility functions (src/utils), such as the tool for rendering llm-generated HTML, converting to PNG and presenting it to critic. All research topics are listed in src/topics.csv. Complete reports for the 100 topics generated with Claude-3.7-Sonnet are available on Google Drive . The following contents are included for each topic: Intermidiate textual report (in Markdown format) Final report (in Markdown and PDF formats) All charts (in HTML and PNG formats) Overall Framework Multimodal DeepResearcher decomposes the task of multimodal report generation into four stages: (A) erative researching about given topic; (B) Exemplar textualization of multimodal reports from human experts using proposed Formal Description of Visualization (FDV) ; (C) Planning; (D) Report Generation, which generates the final report with crafting, coding and iterative refinement. Formal Description of Visualization (FDV) We propose FDV, a structured textual representation of charts that enables Large Language Models to learn from and generate diverse, high-quality visualizations. Experiments Our task requires generating a multimodal report from scratch, which is infeasible with direct prompting or existing deep research frameworks. We incorporate our researching module and adapt the framework of DataNarrative accordingly to establish our baseline. We develop both automatic evaluation (MLLM-as-a-judge) and human evaluation with five dedicated evaluation metrics. Here are the results: Automatic evaluation results: Human Evaluation results: Acknowledgement The demo website is built upon the template from Tailwind Nextjs Starter Blog . The original README for the template is here . We are inspired by many previous works. To name a few, DataNarrative , PPT Agent and previous deep research frameworks, such as deep-research , node-DeepResearch and manus . Citation If you find our work interesting, consider citing us via: @inproceedings { yang2025multimodal , title = { Multimodal deepresearcher: Generating text-chart interleaved reports from scratch with agentic framework } , author = { Yang, Zhaorui and Pan, Bo and Wang, Han and Wang, Yiyao and Liu, Xingyu and Weng, Luoxuan and Feng, Yingchaojie and Feng, Haozhe and Zhu, Minfeng and Zhang, Bo and Chen, Wei } , booktitle = { Proceedings of the AAAI Conference on Artificial Intelligence } , year = { 2026 } } About [AAAI 2026] Multimodal Deepresearcher: Generating Text-Chart Interleaved Reports From Scratch with Agentic Framework rickyang1114.github.io/multimodal-deepresearcher/ Topics agentic-framework deepresearch multimodal-deepresearch Resources Readme License MIT license Uh oh! There was an error while loading. Please reload this page . Activity Stars 57 stars Watchers 0 watching Forks 3 forks Report repository Contributors Uh oh! There was an error while loading. 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