3 citations · 3 across the 4 of their papers we have counts for
5 papers
Rethinking the Implications of Human Feedback for Preference Learning in Human-Robot Collaboration
Qiping Zhang, Kate Candon, Debasmita Ghose +1
In Human-Robot Interaction, the standard approach to learn a reward model that represents human preferences for robot behavior consists of three steps. First, the robot collects li…
Robots Influencing Humans to Reveal their Goals during Collaboration and Competition
Debasmita Ghose, Oz Gitelson, Michal Lewkowicz +3
We propose a unified strategy for fast goal inference in human-robot interaction. The core idea is to drive the human toward Critical Decision Points (CDPs)-states where competing…
Open-Ended Goal Inference through Actions and Language for Human-Robot Collaboration
Debasmita Ghose, Oz Gitelson, Marynel Vazquez +1
To collaborate with humans, robots must infer goals that are often ambiguous, difficult to articulate, or not drawn from a fixed set. Prior approaches restrict inference to a prede…
I've Changed My Mind: Robots Adapting to Changing Human Goals during Collaboration
Debasmita Ghose, Oz Gitelson, Ryan Jin +3
For effective human-robot collaboration, a robot must align its actions with human goals, even as they change mid-task. Prior approaches often assume fixed goals, reducing goal pre…
Predicting Human Perceptions of Robot Performance During Navigation Tasks
Qiping Zhang, Nathan Tsoi, Mofeed Nagib +4
Understanding human perceptions of robot performance is crucial for designing socially intelligent robots that can adapt to human expectations. Current approaches often rely on sur…