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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Online-Zugang: | https://arxiv.org/abs/2509.05721 |
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| _version_ | 1866914141887791104 |
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| author | Gyarmati, Péter Ferenc Moritz, Dominik Möller, Torsten Koesten, Laura |
| author_facet | Gyarmati, Péter Ferenc Moritz, Dominik Möller, Torsten Koesten, Laura |
| contents | To address the brittleness of monolithic AI agents, our prototype for automated visual data reporting explores a Human-AI Partnership model. Its hybrid, multi-agent architecture strategically externalizes logic from LLMs to deterministic modules, leveraging the rule-based system Draco for principled visualization design. The system delivers a dual-output: an interactive Observable report with Mosaic for reader exploration, and executable Marimo notebooks for deep, analyst-facing traceability. This granular architecture yields a fully automatic yet auditable and steerable system, charting a path toward a more synergistic partnership between human experts and AI. For reproducibility, our implementation and examples are available at https://peter-gy.github.io/VISxGenAI-2025/. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_05721 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Composable Agentic System for Automated Visual Data Reporting Gyarmati, Péter Ferenc Moritz, Dominik Möller, Torsten Koesten, Laura Human-Computer Interaction To address the brittleness of monolithic AI agents, our prototype for automated visual data reporting explores a Human-AI Partnership model. Its hybrid, multi-agent architecture strategically externalizes logic from LLMs to deterministic modules, leveraging the rule-based system Draco for principled visualization design. The system delivers a dual-output: an interactive Observable report with Mosaic for reader exploration, and executable Marimo notebooks for deep, analyst-facing traceability. This granular architecture yields a fully automatic yet auditable and steerable system, charting a path toward a more synergistic partnership between human experts and AI. For reproducibility, our implementation and examples are available at https://peter-gy.github.io/VISxGenAI-2025/. |
| title | A Composable Agentic System for Automated Visual Data Reporting |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2509.05721 |