activity
20162024
most citedUnderstanding Entrainment in Human Groups: Optimising Human-Robot Collaboration from Lessons Learned during Human-Human Collaboration

13 citations · 26 across the 10 of their papers we have counts for

collaborators

10 papers

cs.HC2024

Automation from the Worker's Perspective

Ben Armstrong, Valerie K. Chen, Alex Cuellar +2

Common narratives about automation often pit new technologies against workers. The introduction of advanced machine tools, industrial robots, and AI have all been met with concern…

cs.RO2024

Object Permanence Filter for Robust Tracking with Interactive Robots

Shaoting Peng, Margaret X. Wang, Julie A. Shah +1

Object permanence, which refers to the concept that objects continue to exist even when they are no longer perceivable through the senses, is a crucial aspect of human cognitive de…

cs.RO2024

Learning with Language-Guided State Abstractions

Andi Peng, Ilia Sucholutsky, Belinda Z. Li +4

We describe a framework for using natural language to design state abstractions for imitation learning. Generalizable policy learning in high-dimensional observation spaces is faci…

cs.HC202413 cited

Understanding Entrainment in Human Groups: Optimising Human-Robot Collaboration from Lessons Learned during Human-Human Collaboration

Eike Schneiders, Christopher Fourie, Stanley Celestin +2

Successful entrainment during collaboration positively affects trust, willingness to collaborate, and likeability towards collaborators. In this paper, we present a mixed-method st…

cs.RO2024

Preference-Conditioned Language-Guided Abstraction

Andi Peng, Andreea Bobu, Belinda Z. Li +5

Learning from demonstrations is a common way for users to teach robots, but it is prone to spurious feature correlations. Recent work constructs state abstractions, i.e. visual rep…

cs.LG2023

Human-Guided Complexity-Controlled Abstractions

Andi Peng, Mycal Tucker, Eoin Kenny +3

Neural networks often learn task-specific latent representations that fail to generalize to novel settings or tasks. Conversely, humans learn discrete representations (i.e., concep…