We present an extension of Triangolazioni (a Cultural Heritage webapp) to enrich curated content with context-dependent, external information provided by Large Language Models (LLMs) within a loosely-coupled architecture agnostic to the LLM. The system supports context-dependent information search and presentation within an architecture agnostic to the exploited LLM.

This paper presents an experiment on the effects of inter-agents emotional alignment, a prerequisite for empathic communication, in Human-Robot Interaction (HRI). We describe a pipeline built around the Pepper robot with the idea of verifying the effect of emotionally-aligned communication toward a user. In particular, our goal is twofold, in that we investigate if and to what extent an emotionally-aligned, empathic dialogue impacts on (i) the communication style of the user, and (ii) the persuasive effectiveness of the robot, intended as its ability to alter or reinforce its interlocutors' attitudes and beliefs about the conversation topic. Both these aspects have been assessed in a controlled experiment with 46 participants, comparing a condition where the robot addresses participants with emotionally neutral sentences with a condition where the robot provides answers tailored to the emotions expressed in participants' input utterances. Results show how emotion alignment acts as an effective trigger for the elicitation of different communication styles of the users but also that, contrary to what we expected, it does not play any persuasive effect.

The paper presents an experiment on the effects of adaptive emotional alignment between agents, considered a prerequisite for empathic communication, in Human-Robot Interaction (HRI). Using the NAO robot, we investigate the impact of an emotionally aligned, empathic, dialogue on these aspects: (i) the robot’s persuasive effectiveness, (ii) the user’s communication style, and (iii) the attribution of mental states and empathy to the robot. In an experiment with 42 participants, two conditions were compared: one with neutral communication and another where the robot provided responses adapted to the emotions expressed by the users. The results show that emotional alignment does not influence users’ communication styles or have a persuasive effect. However, it significantly influences attribution of mental states to the robot and its perceived empathy.

In this paper, we describe an empirical evaluation of the user's perceived usefulness of recommendations for configuration tasks in a smart home scenario. Our results suggest that while overall recommendations help improve the performance in the task, the psychological traits of Self-efficacy and Need for Cognition play an important role in determining the perceived usefulness of the recommendations. These effects are somehow different from those reported in other studies where recommendations are provided for a choice task rather than a constructive task. Thus, our results offer evidence regarding the importance of incorporating the evaluation of personality traits into the design of configuration constructive tasks in order to make informed decisions on whether and how to provide users with recommendations. Additionally, they show that it is crucial to take into account the nature of the task and, where possible, individual competencies.

This paper describes the Nao_PRM application aimed at expanding the limited functionality of the simulated Nao robot, already integrated into the Choregraphe application, creating a robot simulation with all the required functionalities for social interaction.

This paper describes the preliminary results of a project aimed to support people with autism in finding city places that match their "sensorial" preferences and aversions. Through a participatory design approach, we designed an interactive map that collects sensorial data about the urban environment exploiting crowdsourcing mechanisms.