GraphiMind: LLM-centric Interface for Information Graphics Design
CoRR(2024)
摘要
Information graphics are pivotal in effective information dissemination and
storytelling. However, creating such graphics is extremely challenging for
non-professionals, since the design process requires multifaceted skills and
comprehensive knowledge. Thus, despite the many available authoring tools, a
significant gap remains in enabling non-experts to produce compelling
information graphics seamlessly, especially from scratch. Recent breakthroughs
show that Large Language Models (LLMs), especially when tool-augmented, can
autonomously engage with external tools, making them promising candidates for
enabling innovative graphic design applications. In this work, we propose a
LLM-centric interface with the agent GraphiMind for automatic generation,
recommendation, and composition of information graphics design resources, based
on user intent expressed through natural language. Our GraphiMind integrates a
Textual Conversational Interface, powered by tool-augmented LLM, with a
traditional Graphical Manipulation Interface, streamlining the entire design
process from raw resource curation to composition and refinement. Extensive
evaluations highlight our tool's proficiency in simplifying the design process,
opening avenues for its use by non-professional users. Moreover, we spotlight
the potential of LLMs in reshaping the domain of information graphics design,
offering a blend of automation, versatility, and user-centric interactivity.
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