3 papers
cs.AI2026
Fix the Mind, Not the Move: Interpretable AI Assistance via Knowledge-Gap Localization
Ayano Hiranaka, Ya-Chuan Hsu, Stefanos Nikolaidis +2
AI assistants in human-AI collaboration often correct suboptimal human actions through behavioral feedback (e.g., alerts or steering-wheel nudges in assistive driving). Such interv…
cs.RO2025
Timing the Message: Language-Based Notifications for Time-Critical Assistive Settings
Ya-Chuan Hsu, Jonathan DeCastro, Andrew Silva +1
In time-critical settings such as assistive driving, assistants often rely on alerts or haptic signals to prompt rapid human attention, but these cues usually leave humans to inter…
cs.RO2025
Integrating Field of View in Human-Aware Collaborative Planning
Ya-Chuan Hsu, Michael Defranco, Rutvik Patel +1
In human-robot collaboration (HRC), it is crucial for robot agents to consider humans' knowledge of their surroundings. In reality, humans possess a narrow field of view (FOV), lim…