ViviDoc: Generating Interactive Documents through Human-Agent Collaboration
📰 ArXiv cs.AI
ViviDoc generates interactive documents through human-agent collaboration, leveraging LLM-based agents to automate content creation
Action Steps
- Identify the requirements for the interactive document, including the type of dynamic visualizations and interactive animations needed
- Utilize LLM-based agents to automate content creation, while providing guidance on the desired output
- Collaborate with human experts to refine and control the generated content, ensuring it meets the requirements and is accurate
- Integrate the generated content into a interactive document framework, such as ViviDoc, to create a cohesive and engaging user experience
Who Needs to Know This
Developers, designers, and domain experts on a team can benefit from ViviDoc as it streamlines the process of creating interactive documents, reducing the need for extensive web development skills
Key Insight
💡 Human-agent collaboration can effectively generate interactive documents, balancing automation with expert control and oversight
Share This
💡 Generate interactive documents with ease using ViviDoc and LLM-based agents!
Key Takeaways
ViviDoc generates interactive documents through human-agent collaboration, leveraging LLM-based agents to automate content creation
Full Article
Title: ViviDoc: Generating Interactive Documents through Human-Agent Collaboration
Abstract:
arXiv:2603.27991v1 Announce Type: cross Abstract: Interactive documents help readers engage with complex ideas through dynamic visualization, interactive animations, and exploratory interfaces. However, creating such documents remains costly, as it requires both domain expertise and web development skills. Recent Large Language Model (LLM)-based agents can automate content creation, but directly applying them to interactive document generation often produces outputs that are difficult to control
Abstract:
arXiv:2603.27991v1 Announce Type: cross Abstract: Interactive documents help readers engage with complex ideas through dynamic visualization, interactive animations, and exploratory interfaces. However, creating such documents remains costly, as it requires both domain expertise and web development skills. Recent Large Language Model (LLM)-based agents can automate content creation, but directly applying them to interactive document generation often produces outputs that are difficult to control
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