Dimitri Ognibene

Università degli Studi di Milano-Bicocca | UNIMIB · Department of Psychology

Proactively perceiving others’ intentions is a crucial skill to effectively interact in unstructured, dynamic and novel environments. This work proposes a first step towards embedding this skill in support robots for search and rescue missions. Predicting the responders’ intentions, indeed, will enable exploration approaches which will identify and...

Non-pharmacological behavioral addictions, such as pathological gambling, videogaming, social networking, or internet use, are becoming major public health concerns. It is not yet clear how behavioral addictions could share many major neurobiological and behavioral characteristics with substance use disorders, despite the absence of direct pharmaco...

Social media have become an integral part of our lives, expanding our interlinking capabilities to new levels. There is plenty to be said about their positive effects. On the other hand, however, some serious negative implications of social media have been repeatedly highlighted in recent years, pointing at various threats to society and its more v...

This study investigates Large Language Models (LLMs) as dynamic Bayesian filters through question-asking experiments inspired by cog-nitive science. We analyse LLMs' inference errors and the evolution of uncertainty across models using repeated sampling. Building on Bertolazzi et al. (2023), we trace LLM belief states during repeated queries, findi...

Robots are increasingly being used in dynamic environments like workplaces, hospitals, and homes. As a result, interactions with robots must be simple and intuitive, with robots’ perception adapting efficiently to human-induced changes. This paper presents a robot control architecture that addresses key challenges in human-robot interaction, with a...

Natural language processing skills of Large Language Models (LLMs) are unprecedented, having wide diffusion and application in different tasks. This pilot study focuses on specializing ChatGPT behavior through a Retrieval-Augmented Generation (RAG) system using the OpenAI custom GPTs feature. The purpose of our chatbot, called Unimib Assistant, is...

This paper presents the iterative development of Habit Coach, a GPT-based chatbot designed to support users in habit change through personalized interaction. Employing a user-centered design approach, we developed the chatbot using a Retrieval-Augmented Generation (RAG) system, which enables behavior personalization without retraining the underlyin...

In recent years, research in the area of human-robot interaction has focused on developing robots capable of understanding complex human instructions and performing tasks in dynamic and diverse environments. These systems have a wide range of applications, from personal assistance to industrial robotics, emphasizing the importance of robots interac...

Robots are increasingly being used in dynamic environments like workplaces, hospitals, and homes. As a result, interactions with robots must be simple and intuitive, with robots perception adapting efficiently to human-induced changes. This paper presents a robot control architecture that addresses key challenges in human-robot interaction, with a...

The purpose of this work is to investigate the soundness and utility of a neural network-based approach as a framework for exploring the impact of image enhancement techniques on visual cortex activation. In a preliminary study, we prepare a set of state-of-the-art brain encoding models, selected among the top 10 methods that participated in The Al...

Active vision is critical for navigating complex, unstructured environments like agricultural fields, where oc-clusions, diverse scales, and unknown elements can obscure task-relevant information. This paper investigates the use of deep learning architectures to estimate information gain and expected loss in continuous, multidimensional observation...

The purpose of this work is to investigate the soundness and utility of a neural network-based approach as a framework for exploring the impact of image enhancement techniques on visual cortex activation. In a preliminary study, we prepare a set of state-of-the-art brain encoding models, selected among the top 10 methods that participated in The Al...

The widespread use of social media has highlighted potential negative impacts on society and individuals, largely driven by recommendation algorithms that shape user behavior and social dynamics. Understanding these algorithms is essential but challenging due to the complex, distributed nature of social media networks as well as limited access to r...

The widespread use of social media has highlighted potential negative impacts on society and individuals, largely driven by recommendation algorithms that shape user behavior and social dynamics. Understanding these algorithms is essential but challenging due to the complex, distributed nature of social media networks as well as limited access to r...

The advent of Artificial Intelligence (AI) has revolutionized multiple sectors including education. The popularization of tools such as ChatGPT has sparked the debate concerning the impact of AI on traditional education and the nature of learning. This paper explores undergraduate students’ attitudes towards AI and ChatGPT acceptance. A descriptive...

LLM-based chatbots represent a significant milestone as the initial point of interaction between artificial intelligence and the general public. These chatbots offer greater flexibility compared to traditional chatbots, yet their behavior deviates notably from human interaction patterns. Current annotation schemas may not be adequately suited to ca...

Theory of Mind (ToM), the ability to attribute beliefs, intentions, or mental states to others, is a crucial feature of human social interaction. In complex environments, where the human sensory system reaches its limits, behaviour is strongly driven by our beliefs about the state of the world around us. Accessing others' mental states, e.g., belie...

The impact of social media on teens' mental health and development raises the need for educational interventions that equip them with the knowledge and skills to cope with dangerous situations. In spite of the growing effort to expand social media literacy among youngsters, social media interventions still rely on conventional methods that tend to...

Can a LLM understand dialogues, in particular from multi-party settings? In this study we explore this question through the pragmatic framework of Dialogue Acts or Speech Acts. Two tasks - classification and prediction of Dialogue Acts an - are tested with zero and few-shot learning on the STAC multi-party corpus that contains over 13000 EDUs (Ele...

Human language interactions involve complex processes beyond pure information exchange, for example, actions aimed at influencing beliefs and behaviors within a communicative context. In this paper, we propose to investigate the dialogue understanding capabilities of large language models (LLMs), particularly in multi-party settings, where challeng...

The advent of Artificial Intelligence (AI) has revolutionized multiple sectors including education. The popularization of tools such as ChatGPT has sparked the debate concerning the impact of AI on traditional education and the nature of learning. This paper explores undergraduate students' attitudes towards AI and ChatGPT acceptance. A descriptive...

Generative Artificial Intelligence (AI) is a rapidly expanding field that aims to develop machines capable of performing tasks that were previously considered unique to humans, such as learning, reasoning, problem-solving, and decision-making. The recent release of several tools based on AI (e.g. ChatGPT) has sparked debates on the potential of thi...

Objective. This study presents a novel methodological approach for incorporating information related to the peripheral sympathetic response into the investigation of neural dynamics. Particularly, we explore how hedonic contextual olfactory stimuli influence the processing of neutral faces in terms of sympathetic response, event-related potentials...

Artificial intelligence’s (AI) progress holds great promise in tackling pressing societal concerns such as health and climate. Large Language Models (LLM) and the derived chatbots, like ChatGPT, have highly improved the natural language processing capabilities of AI systems allowing them to process an unprecedented amount of unstructured data. Howe...

The introduction of ChatGPT into educational settings has sparked considerable controversy due to its exceptional performance and ability to streamline task management for both teachers and students. However, the success of ChatGPT has also given rise to apprehensions regarding the potential for AI-assisted cheating, resulting in restrictions on it...

This study examines the modulatory effect of contextual hedonic olfactory stimuli on the visual processing of neutral faces using event-related potentials (ERPs) and effective connectivity analysis. The aim is to investigate how odors' valence influences the cortical connectivity underlying face processing, and the role arousal enhanced by faces pl...

Social Media Artificial Intelligence algorithms provide users with engaging and personalized content. Yet, the personalization of algorithms may have a negative impact on users who lack AI literacy. The limited understanding of SM algorithms among the population suggest that adolescents are more likely to place blind trust in the information they c...

Artificial intelligence's progress holds great promise in assisting society in addressing pressing societal issues. In particular Large Language Models (LLM) and the derived chatbots, like ChatGPT, have highly improved the natural language processing capabilities of AI systems allowing them to process an unprecedented amount of unstructured data. T...

Educational chatbots come with a promise of interactive and personalized learning experiences, yet their development has been limited by the restricted free interaction capabilities of available platforms and the difficulty of encoding knowledge in a suitable format. Recent advances in language learning models with zero-shot learning capabilities,...

Social media are offering new opportunities for communication and interaction way beyond what was possible only a few years ago. However, social media are also virtual spaces where young people are exposed to a variety of threats. Digital addiction, discrimination, hate speech, misinformation, polarization as well as manipulative influences of algo...

The provision of toxic content and misinformation is a frequent phenomenon in current social media with specific impact and risks for younger users. We report on efforts taken in the project Courage to mitigate and overcome these threats through dedicated educational technology inspired by psychological and pedagogical approaches. The aim is to emp...

We present a digital media literacy activity composed of (i) an educational talk and (ii) a game-based activity. The aim is to support teachers in developing learning activities to increase awareness of social media threats among students. Through this activity students directly experience phenomena like echo chambers and filter bubbles that can be...

Social media platforms provide opportunities for users across the world to connect and communicate between them and engage into acts of social support and entertainment. Yet it can also bring negative consequences as it has been associated with poor mental health and life dissatisfaction. This underlines the importance of delivering social media li...

In human spatial awareness, information appears to be represented according to 3-D projective geometry. It structures information integration and action planning within an internal representation space. The way different first person perspectives of an agent relate to each other, through transformations of a world model, defines a specific percepti...

Using a socio-psychological approach and drawing on the Intergroup Threat Theory, our study demonstrates that when faced with ChatGPT's ability to reproduce the complexity of human language and conversation, participants reported significantly higher levels of negative emotions than those in the control group. These negative emotions predicted part...

Natural language processing and other areas of artificial intelligence have seen staggering progress in recent years, yet much of this is reported with reference to somewhat limited benchmark datasets. We see the deployment of these techniques in realistic use cases as the next step in this development. In particular, much progress is still needed...

Creating autonomous robots that can actively explore the environment, acquire knowledge and learn skills continuously is the ultimate achievement envisioned in cognitive and developmental robotics. Their learning processes should be based on interactions with their physical and social world in the manner of human learning and cognitive development....

In a digitally led society, where social media consumption is constantly increasing, users are confronted not only with positive, but also with toxic content and dynamics like cyberbullying, racism, hate speech, or fake news [1,2,3]. Oftentimes, users are not aware of the severity (e.g., racist or homophobic comments) or level of manipulation (e...

In complex environments, where the human sensory system reaches its limits, our behaviour is strongly driven by our beliefs about the state of the world around us. Accessing others' beliefs, intentions, or mental states in general, could thus allow for more effective social interactions in natural contexts. Yet these variables are not directly obse...

Social media platforms provide opportunities for users across the world to connect and communicate between them and engage into acts of social support and entertainment. Yet it can also bring negative consequences as it has been associated with poor mental health and life dissatisfaction. This underlines the importance of delivering social media li...

ocial media are a game changer in the communication arena in terms of quan�tity, quality and origin of information users are exposed to. Yet, it’s not clear the outcome of multiple and continued interactions between users and information personalisation systems. These systems may skew the distribution of content and contacts presented to the users....

Social media, defined as “computer-mediated communication channels that allow users to engage in social interaction with broad and narrow audiences in real time or asynchronously” [1], are an integral part of our everyday lives offering new opportunities for communication and interaction way beyond what was possible only a few years ago. 98% of...

Monitoring crop fields to map features like weeds can be efficiently performed with unmanned aerial vehicles (UAVs) that can cover large areas in a short time due to their privileged perspective and motion speed. However, the need for high-resolution images for precise classification of features (e.g., detecting even the smallest weeds in the field...

Monitoring crop fields to map features like weeds can be efficiently performed with unmanned aerial vehicles (UAVs) that can cover large areas in a short time due to their privileged perspective and motion speed. However, the need for high-resolution images for precise classification of features (e.g., detecting even the smallest weeds in the field...

Social demand for robots to be our partners in daily life has been rapidly increasing. Cognitive robotics should play a major role in making robots our partners. To discuss the role of cognitive robotics, we organized the round table in December 2020. This review paper aimed at clarifying the role of cognitive robotics summarizing the discussion in...

Social media has become an important part of adolescents’ lives, with an increasing number of teenagers spending a great part of their time creating, sharing, and socializing with online content. Although the popularity of social media keeps growing, different studies identified threats and dangers that exist in such networks. From harmful content...

Recent times are witnessing the emergence of indoor sites with extenuating circumstances that place a strict time constraint on mobile robots to reach a target while covering a given area. This has created a global demand to equip mobile robots with the ability to autonomously plan a coverage path to reach the static target effectively and efficien...

Social media (SM) have become an integral part of our lives, expanding our inter-linking capabilities to new levels. There is plenty to be said about their positive effects. On the other hand however, some serious negative implications of SM have repeatedly been highlighted in recent years, pointing at various SM threats for society, and its teenag...

Despite the recent advancement in the social robotic field, important limitations restrain its progress and delay the application of robots in everyday scenarios. In the present paper, we propose to develop computational models inspired by our knowledge of human infants’ social adaptive abilities. We believe this may provide solutions at an archite...

In this paper, we propose a design methodology for one-class classifiers using an ensemble-of-classifiers approach. The objective is to select the best structures created during the training phase using an ensemble of spanning trees. It takes the best classifier, partitioning the area near a pattern into $\gamma^{\gamma-2}$ sub-spaces and combining...

Great advancements have been achieved in the field of robotics, however, main challenges remain, including building robots with an adaptive Theory of Mind (ToM). In the present paper, seven current robotic architectures for human-robot interactions were described as well as four main functional advantages of equipping robots with an adaptive ToM. T...

Despite the recent advancement in the social robotic field, important limitations restrain its progress and delay the application of robots in everyday scenarios. In the present paper, we propose to develop computational models inspired by our knowledge of human infants' social adaptive abilities. We believe this may provide solutions at an archite...

Proactively perceiving others' intentions is a crucial skill to effectively interact in unstructured, dynamic and novel environments. This work proposes a first step towards embedding this skill in support robots for search and rescue missions. Predicting the responders' intentions, indeed, will enable exploration approaches which will identify and...

One-class classifiers are trained only with target class samples. Intuitively, their conservative modeling of the class description may benefit classical classification tasks where classes are difficult to separate due to overlapping and data imbalance. In this work, three methods leveraging on the combination of one-class classifiers based on non-...

One-class classifiers are trained with target class only samples. Intuitively, their conservative modelling of the class description may benefit classical classification tasks where classes are difficult to separate due to overlapping and data imbalance. In this work, three methods are proposed which leverage on the combination of one-class classif...

Several decision-making vulnerabilities have been identified as underlying causes for addictive behaviours, or the repeated execution of stereotyped actions despite their adverse consequences. These vulnerabilities are mostly associated with brain alterations caused by the consumption of substances of abuse. However, addiction can also happen in th...

Several decision-making vulnerabilities have been identified as underlying causes for addictive behaviours, or the repeated execution of stereotyped actions despite their adverse consequences. These vulnerabilities are mostly associated with brain alterations caused by the consumption of substances of abuse. However, addiction can also happen in th...

Perception is a complex, neural mechanism that requires organization and interpretation of input meaning and it has been a key topic in medicine, neuroscience and philosophy for centuries. Gestalt psychology proposed that the underlying mechanism is a constructive process that depends on both input of stimuli and the sensory-motor state of the agen...

Addiction is characterized by a profound intersubject (phenotypic) variability in the expression of addictive symptomatology and propensity to relapse following treatment. However, laboratory investigations have primarily focused on common neural substrates in addiction and have not yet been able to identify mechanisms that can account for the mult...