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
How people interpret robot errors may depend not only on the observed behavior, but also on the robot's morphology and on whether the error is framed as unintentional or intentional. Prior works showed that human-like robots can elicit stronger mind attribution and deceptive robot behavior can encourage intentional int...
Raffaella Esposito, Ashita Ashok, Alessandra Rossi 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
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
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
: Artificial Neural Networks (ANNs) are increasingly used in psychological assessment to score measures, classify clinical presentations, monitor symptoms, estimate risk, and tailor interventions. This scoping review maps ANN applications in psychological assessment and diagnosis and examines their relevance to psychia...
Monica Casella, Raffaella Esposito, M. Ponticorvo· International Journal of Men...· 0 citations
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