1 citations · 2 across the 4 of their papers we have counts for
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How Users Perceive Mixed-Initiative AI: Attitudes Toward Assistance in Problem Solving
Yunhao Luo, Arthur Caetano, Avinash Ajit Nargund +2
In mixed-initiative systems, the mode of AI assistance delivery can be as consequential as the assistance itself. We investigated two assistance delivery modes: on-demand help (use…
Embedded vs. Situated: An Evaluation of AR Facial Training Feedback
Avinash Ajit Nargund, Andrea M. Park, Tobias Höllerer +1
While augmented reality (AR) research demonstrates benefits of embedded visualizations for gross motor training, its applicability to facial exercises remains under-explored. Provi…
Exploration of Radar-based Obstacle Visualizations to Support Safety and Presence in Camera-Free Outdoor VR
Avinash Ajit Nargund, Andrew L. Huard, Tobias Höllerer +1
Outdoor virtual reality (VR) places users in dynamic physical environments where they must remain aware of real-world obstacles, including static structures and moving bystanders,…
Understanding Mode Switching in Human-AI Collaboration: Behavioral Insights and Predictive Modeling
Avinash Ajit Nargund, Arthur Caetano, Kevin Yang +6
Human-AI collaboration is typically offered in one of two of user control levels: guidance, where the AI provides suggestions and the human makes the final decision, and delegation…