4 papers
ProMemAssist: Exploring Timely Proactive Assistance Through Working Memory Modeling in Multi-Modal Wearable Devices
Kevin Pu, Ting Zhang, Naveen Sendhilnathan +3
Wearable AI systems aim to provide timely assistance in daily life, but existing approaches often rely on user initiation or predefined task knowledge, neglecting users' current me…
Less or More: Towards Glanceable Explanations for LLM Recommendations Using Ultra-Small Devices
Xinru Wang, Mengjie Yu, Hannah Nguyen +10
Large Language Models (LLMs) have shown remarkable potential in recommending everyday actions as personal AI assistants, while Explainable AI (XAI) techniques are being increasingl…
Implicit gaze research for XR systems
Naveen Sendhilnathan, Ajoy S. Fernandes, Michael J. Proulx +1
Although eye-tracking technology is being integrated into more VR and MR headsets, the true potential of eye tracking in enhancing user interactions within XR settings remains rela…
Explainable Interfaces for Rapid Gaze-Based Interactions in Mixed Reality
Mengjie Yu, Dustin Harris, Ian Jones +12
Gaze-based interactions offer a potential way for users to naturally engage with mixed reality (XR) interfaces. Black-box machine learning models enabled higher accuracy for gaze-b…