In Human-Robot Collaboration, failures that are not explained or handled with alternative strategies can undermine user trust and interaction quality. Despite recent advances in LLM-based task planning, failures are often treated as terminal events, leading to non-transparent robot behaviors. This work investigates how...
Luca Raggioli, Emanuele Ciro Muto, Raffaella Esposito et al.· IEEE International Symposium...· 0 citations
In human-robot interaction, achieving a goal may require a robot to engage in competitive behaviors toward its human partner. In some cases, it is important for the robot to balance firmness with an amicable attitude to avoid causing discomfort to the user. In others, it might be necessary to push the user to act more...
Luca Raggioli, Antimo Cantiello, Francesco Ciccarelli et al.· IEEE International Symposium...· 0 citations
While the term may carry negative connotations, robot deception has been shown to elicit beneficial behavioural changes in people when trust is established. This study investigates trust and deception in human-robot interactions, focusing on how individuals recognize and respond to multimodal deceptive behaviours in a...
Alessandra Rossi, Antonio Vecce, Silvia Rossi· IEEE International Symposium...· 0 citations
Student engagement detection is an important component of adaptive learning systems, yet it remains challenging because observable behaviours can have different meanings depending on the context. Most existing approaches primarily infer engagement from visual cues, while other contextual information is less frequently...
Andreas Naoum, Mario Barbato, Lily-Cannelle Mathieu et al.· Proceedings of the 28th Inte...· 1 citation
Student engagement estimation is a key challenge in online education, where instructors have limited access to the behavioral cues available in traditional classrooms. This paper presents our approach to the Context-Aware Student Engagement Detection (CASED) Challenge, which aims to estimate continuous engagement from...
L. D'Arco, Raffaella Esposito, Diego Veneruso et al.· Proceedings of the 28th Inte...· 0 citations
Multimodal fusion systems for human–robot interaction predominantly rely on snapshot-level features that capture what nonverbal signals are present at a given moment, ignoring when they occur, how long they last, and in what order they unfold. Nevertheless, the temporal dynamics of human behaviour may convey communicat...
Eunyoung Hwang, Alessandra Rossi, Silvia Rossi· Proceedings of the 28th Inte...· 0 citations
Student engagement detection is an important component of adaptive learning systems, yet it remains challenging because observable behaviours can have different meanings depending on the context. Most existing approaches primarily infer engagement from visual cues, while other contextual information is less frequently...
Andreas Naoum, Mario Barbato, Lily-Cannelle Mathieu et al.· 0 citations
Student engagement estimation is a key challenge in online education, where instructors have limited access to the behavioral cues available in traditional classrooms. This paper presents our approach to the Context-Aware Student Engagement Detection (CASED) Challenge, which aims to estimate continuous engagement from...
L. D'Arco, Raffaella Esposito, Diego Veneruso et al.· 0 citations
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