AVA: Towards Autonomous Visualization Agents through Visual Perception-Driven Decision-Making

dc.contributor.authorLiu, Shusenen_US
dc.contributor.authorMiao, Haichaoen_US
dc.contributor.authorLi, Zhiminen_US
dc.contributor.authorOlson, Matthewen_US
dc.contributor.authorPascucci, Valerioen_US
dc.contributor.authorBremer, Peer-Timoen_US
dc.contributor.editorAigner, Wolfgangen_US
dc.contributor.editorArchambault, Danielen_US
dc.contributor.editorBujack, Roxanaen_US
dc.date.accessioned2024-05-21T08:18:38Z
dc.date.available2024-05-21T08:18:38Z
dc.date.issued2024
dc.description.abstractWith recent advances in multi-modal foundation models, the previously text-only large language models (LLM) have evolved to incorporate visual input, opening up unprecedented opportunities for various applications in visualization. Compared to existing work on LLM-based visualization works that generate and control visualization with textual input and output only, the proposed approach explores the utilization of the visual processing ability of multi-modal LLMs to develop Autonomous Visualization Agents (AVAs) that can evaluate the generated visualization and iterate on the result to accomplish user-defined objectives defined through natural language. We propose the first framework for the design of AVAs and present several usage scenarios intended to demonstrate the general applicability of the proposed paradigm. Our preliminary exploration and proof-of-concept agents suggest that this approach can be widely applicable whenever the choices of appropriate visualization parameters require the interpretation of previous visual output. Our study indicates that AVAs represent a general paradigm for designing intelligent visualization systems that can achieve high-level visualization goals, which pave the way for developing expert-level visualization agents in the future.en_US
dc.description.number3
dc.description.sectionheadersWorkflows and Decision Making
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume43
dc.identifier.doi10.1111/cgf.15093
dc.identifier.issn1467-8659
dc.identifier.pages12 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.15093
dc.identifier.urihttps://diglib.eg.org/handle/10.1111/cgf15093
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.titleAVA: Towards Autonomous Visualization Agents through Visual Perception-Driven Decision-Makingen_US
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