[2410.22177] Analyzing Multimodal Interaction Strategies for LLM-Assisted Manipulation of 3D Scenes

Computer Science > Human-Computer Interaction arXiv:2410.22177 (cs) [Submitted on 29 Oct 2024 (v1), last revised 8 Apr 2026 (this version, v2)] Title:Analyzing Multimodal Interaction Strategies for LLM-Assisted Manipulation of 3D Scenes Authors:Junlong Chen, Jens Grubert, Per Ola Kristensson View a PDF of the paper titled Analyzing Multimodal Interaction Strategies for LLM-Assisted Manipulation of 3D Scenes, by Junlong Chen and Jens Grubert and Per Ola Kristensson View PDF HTML (experimental) Abstract:As more applications of large language models (LLMs) for 3D content for immersive environments emerge, it is crucial to study user behaviour to identify interaction patterns and potential barriers to guide the future design of immersive content creation and editing systems which involve LLMs. In an empirical user study with 12 participants, we combine quantitative usage data with post-experience questionnaire feedback to reveal common interaction patterns and key barriers in LLM-assisted 3D scene editing systems. We identify opportunities for improving natural language interfaces in 3D design tools and propose design recommendations for future LLM-integrated 3D content creation systems. Through an empirical study, we demonstrate that LLM-assisted interactive systems can be used productively in immersive environments. Comments: Subjects: Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI) Cite as: arXiv:2410.22177 [cs.HC]   (or arXiv:2410.22177v2 [cs.HC] for th...