MindTrellis: Co-Creating Knowledge Structures with AI through Interactive Visual Exploration

• URL: http://arxiv.org/abs/2604.23129v1
• Date: Sat, 25 Apr 2026 03:53:26 GMT
• Title: MindTrellis: Co-Creating Knowledge Structures with AI through Interactive Visual Exploration
• Abstract summary: We present MindTrellis, an interactive visual system where users and AI collaboratively build a dynamic knowledge graph.<n>Users can query the graph to retrieve document-grounded information, and contribute by introducing new concepts, modifying relationships, and reorganizing the hierarchy to reflect their developing understanding.<n>In a user study where 12 participants created slide decks, MindTrellis outperformed retrieval-only baselines in knowledge organization and cognitive load, as measured by expert ratings of content coverage and structural quality.
• Score: 19.586529329374716
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Knowledge workers face increasing challenges in synthesizing information from multiple documents into structured conceptual understanding. This process is inherently iterative: users explore content, identify relationships between concepts, and continuously reorganize their mental models. However, current approaches offer limited support. LLM-based systems let users query information but not shape how knowledge is organized; manual tools like mind maps support structure creation but lack intelligent assistance. This leaves an open opportunity: supporting collaborative construction where users and AI jointly develop an evolving knowledge representation. We present MindTrellis, an interactive visual system where users and AI collaboratively build a dynamic knowledge graph. Users can query the graph to retrieve document-grounded information, and contribute by introducing new concepts, modifying relationships, and reorganizing the hierarchy to reflect their developing understanding. In a user study where 12 participants created slide decks, MindTrellis outperformed retrieval-only baselines in knowledge organization and cognitive load, as measured by expert ratings of content coverage and structural quality.

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