AI 中文总结
研究LLM辅助沉浸式3D场景编辑中的虚构，通过对24名非专业用户的探索性研究构建分类法，报告其普遍性与破坏性，定义感知-现实差距结构，强调负载下虚构意识饱和度，得出对未来系统减轻虚构的设计启示。
AI 中文摘要
大语言模型（LLMs）越来越多地融入沉浸式环境和设计工作流程，在非专业用户快速场景原型制作和无障碍设计场景理解能力等领域提供了应用前景。然而，许多整合LLMs的沉浸式空间工作流程会出现错误，可能导致用户沮丧、失去信任和安全问题。本文研究了沉浸式3D场景编辑中LLM虚构这一未充分探索的领域。通过对24名非专业用户的探索性研究，构建了LLM辅助沉浸式3D场景编辑中观察到的不同类型虚构的分类法。报告了它们的普遍性和破坏性，并定义了感知-现实差距结构，以帮助理解虚构实际发生与感知发生之间的差距。强调了在负载下观察到的虚构意识饱和度，并通过讨论对未来LLM辅助的沉浸式3D场景系统中减轻虚构的设计影响得出结论。
英文摘要
Large language models (LLMs) are being increasingly integrated into immersive environments and design workflows, providing application prospects in areas such as rapid scene prototyping for non-expert users and scene understanding capabilities for accessibility design. While many workflows that incorporate LLMs in immersive spaces are proposed, such systems can exhibit errors, potentially resulting in frustration, loss of user trust, and compromised user safety. This paper studies the underexplored area of LLM confabulations in immersive 3D scene editing contexts. Through an exploratory study with 24 non-expert users, we construct a taxonomy of the different types of confabulation observed in LLM-assisted immersive 3D scene editing. We report their prevalence and disruptiveness, and define the construct perception-reality gap to help understand the gap between the actual and perceived occurrence of confabulations. We highlight the observed saturation of confabulation awareness under load and conclude by discussing design implications for confabulation mitigation in future LLM-assisted systems in immersive 3D scenes.
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