Conversations in Space: Structuring Non-Linear LLM Interactions on a Canvas
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Computer Science > Human-Computer Interaction
Title:Conversations in Space: Structuring Non-Linear LLM Interactions on a Canvas
Abstract:Conversational interfaces powered by large language models (LLMs) are widely used for ideation and analysis, yet their linear structure limits exploration of alternatives and management of long-running interactions. We present CanvasConvo, a conversational interface concept that transforms linear chat into a branching conversation tree embedded in a spatial canvas. CanvasConvo enables users to explore what-if scenarios by branching directly from conversational content, supporting parallel development of alternative directions. These branches are visualized on a canvas while remaining integrated with a familiar chat interface, allowing users to switch between linear and non-linear interaction. Features such as timeline-based navigation, automatic tagging and summarization, and context-aware controls (e.g., goals, reusable prompts) support structured interaction and continuity. We evaluated CanvasConvo in a 5-7 day field study with 24 participants. Our findings highlight how non-linear conversational structures support exploratory workflows and different interactions in LLM-based work.
| Subjects: | Human-Computer Interaction (cs.HC); Computation and Language (cs.CL) |
| Cite as: | arXiv:2605.15848 [cs.HC] |
| (or arXiv:2605.15848v1 [cs.HC] for this version) | |
| https://doi.org/10.48550/arXiv.2605.15848
arXiv-issued DOI via DataCite (pending registration)
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Submission history
From: Rifat Mehreen Amin [view email][v1] Fri, 15 May 2026 11:01:31 UTC (1,082 KB)
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