CONDA: Introducing Context-Aware Decision Making Assistant in Virtual Reality for Interior Renovation

Customized interiors enhance quality of life and self-expression, driving demand for VR-based design solutions. However, scant research exists on exploiting contextual cues in VR to aid decision making. Consequently, we propose CONDA, a context-aware assistant which leveraging LLMs to support interior renovation decisions. Specifically, we reconstruct users’ homes in VR and provide CONDA with stylistic details and spatial layouts, allowing it to predict furniture labels based on the decision scenario. Besides, we devise various modes to comprehensively express users’ purchasing preferences. Finally, CONDA recommend compatible items based on the label matching algorithm, and generate multi-dimensional explanations. A 30-user study reveals contextual completeness and preference diversity critically influence recommendation quality and decision behaviors, with 90% praising CONDA’s performance and all expressing daily-use intent. Overall, we validated the efficacy and practicality of CONDA, deriving universal design insights for VR decision-support systems and establishing new research directions.CCS Concepts Human-centered computing (Formula presented.) Virtual reality Computing methodologies (Formula presented.) Natural language generation Applied computing (Formula presented.) Computer-aided design.