Analyzing Multimodal Interaction Strategies for LLM-Assisted Manipulation of 3D Scenes
This work addresses interaction challenges for users of LLM-integrated 3D content creation tools, but it is incremental as it focuses on empirical analysis without introducing new methods.
The study tackled the problem of understanding user behavior in LLM-assisted 3D scene editing systems through an empirical user study with 12 participants, revealing common interaction patterns and key barriers to guide future design improvements.
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.