From the 1 of 7 linked papers with an AI index.
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ERR@HRI 3.0 Challenge: Multimodal Detection of Errors and Anticipation in Human-Robot Interactions
Maria Teresa Parreira, Micol Spitale, Maia Stiber +5
The paper presents the ERR@HRI 3.0 Challenge, which provides two naturalistic video datasets for developing multimodal machine learning models that detect bystander reactions to ro…
Signal or 'Noise': Human Reactions to Robot Errors in the Wild
Maia Stiber, Sameer Khan, Russell Taylor +1
In the real world, robots frequently make errors, yet little is known about people's social responses to errors outside of lab settings. Prior work has shown that social signals ar…
ERR@HRI 2.0 Challenge: Multimodal Detection of Errors and Failures in Human-Robot Conversations
Shiye Cao, Maia Stiber, Amama Mahmood +5
The integration of large language models (LLMs) into conversational robots has made human-robot conversations more dynamic. Yet, LLM-powered conversational robots remain prone to e…
Xpress: A System For Dynamic, Context-Aware Robot Facial Expressions using Language Models
Victor Nikhil Antony, Maia Stiber, Chien-Ming Huang
Facial expressions are vital in human communication and significantly influence outcomes in human-robot interaction (HRI), such as likeability, trust, and companionship. However, c…
Robot Error Awareness Through Human Reactions: Implementation, Evaluation, and Recommendations
Maia Stiber, Russell Taylor, Chien-Ming Huang
Effective error detection is crucial to prevent task disruption and maintain user trust. Traditional methods often rely on task-specific models or user reporting, which can be infl…
ERR@HRI 2024 Challenge: Multimodal Detection of Errors and Failures in Human-Robot Interactions
Micol Spitale, Maria Teresa Parreira, Maia Stiber +7
Despite the recent advancements in robotics and machine learning (ML), the deployment of autonomous robots in our everyday lives is still an open challenge. This is due to multiple…