The conference is open to Session and Track proposals. Please click HERE to submit your proposal.
Track: Linguistic and Behavioural Interaction Analysis in Empathic Systems
Track Organizers:
Anna Esposito (Università Vanvitelli/IIASS, Italy)
Antonietta M. Esposito (Osservatorio Vesuviano, Sezione di Napoli,Italy)
Maria Koutsombogera (Trinity College Dublin, Ireland)
Gennaro Cordasco (Università Vanvitelli/IIASS, Italy),
Mauro Maldonato (Università di Napoli Federico II, Italy)
Carl Vogel (Trinity College Dublin, Ireland)
Scope:
This track aims at gathering original works on communication, actions, perception and emotion from experimental and theoretical points of view. The ultimate goal of this research is to provide computational paradigms that may
implement culture-specific, trustful, credible, satisfactory and emotionally coloured human-machine interfaces and artificial agents.
The topics include, but are not limited to:
Cross-cultural processing of social signals
Linguistic and social interactional exchanges
Social Robotics: analysis and applications
Human behaviour: Analysis and understanding
Linguistic sentiment analysis
Changes in sentiment expressions
Cognitive Economy
Group behaviour, group cognition and cultural specificity
Influence of context on perception, memory and decision making
Cognitive systems for multimodal signal analysis
Nonlinear processing of audio-video social signals
Multimodal social signal processing
Other…..
Session: Social Simulation with Large Language Models
Track Organizers:
Ferenc Kiss (Foundation for Information Society, Hungary)
Overview:
The advent of large language models (LLMs) trained on vast amounts of human data has revealed their ability to exhibit not only advanced linguistic capabilities but also cognitive strategies and biases that resemble human behavior. This remarkable characteristic has catalyzed the emergence of a new field: social simulation using LLMs.
By employing fine-grained persona-based prompts, researchers in the social sciences are leveraging LLMs to simulate human behaviors with increasing accuracy. Early findings suggest strong evidence of validity, particularly in modeling multi-actor social scenarios on scales previously unimaginable—up to millions of participants. This positions LLMs as a powerful new tool for social science, akin to how the microscope revolutionized biology.
Promise and Potential:
Social simulation with LLMs offers groundbreaking opportunities, including:
- Scalability: Modeling interactions at population-scale levels with remarkable precision.
- Interdisciplinary Exploration: Bridging computational tools and social science methodologies.
- Novel Insights: Exploring emergent behaviors, complex dynamics, and societal patterns.
Goals of This Section:
- Connect Researchers: Foster collaboration among experts from diverse fields such as social sciences, machine learning, and computational modeling.
- Showcase Potential: Highlight the promise and transformative capabilities of LLM-based social simulations.
- Define Key Directions: Discuss critical research avenues, methodological challenges, and ethical considerations.
- Raise Awareness: Promote understanding of this emerging field among a broad academic audience, focusing on those currently unaware of its potential.
Planned action:
Given the nascent nature of the field, this section aims to invite a carefully curated group of researchers. This approach ensures impactful discussions and fosters an interdisciplinary community at the forefront of LLM-based social simulation.
Session: Cognitive Aspects of Virtual Reality
Track Organizers:
Ildikó Horváth & Anna Sudár (Corvinus University of Budapest, Hungary)
Scope:
Cognitive Aspects of Virtual Reality (cVR) investigates the next phases of IT evolution characterized by a transition from digital environments based on 2D graphical user interfaces (e.g. windows, images, 2D widgets) to 3D spaces which represent a higher-level integration of VR/AR/MR/Metaverse/IoD systems, human spatial cognition, the 2D digital world (i.e. Web 2.0, Web 3.0) and artificial intelligence (AI). A primary focus of cVR is how this transition simultaneously makes use of and augments human capabilities, including psychological, cognitive and social capabilities – especially capabilities linked to a deeper understanding of geometric, temporal and semantic relationships. By extension, cVR further investigates the effects of these changes in human and AI capabilities with respect to a variety of sectors including education, commerce, healthcare, industrial production and others.
Track: Organic human-robot interaction for Social robotics
Track Organizers:
Csilla Csukonyi (psychologist), University of Debrecen
Niitsuma Mihoko (etho-roboticist), Chuo University
Almusawi Husam Abdulkareem (robot specialist) University of Debrecen,
Scope:
Social robots, especially service and assistance robots, will soon become part of our daily lives, for example in the hospitality industry or in elderly care roles. With the advent of Industry 5.0, robots equipped with social skills may also appear in factories. With the ever-expanding role of social robots and other artificial agents (including software-based, virtually displayed agents), the development of appropriate communication becomes an urgent task in the field of human-robot and human-computer interaction as well. The need to communicate more and more naturally with robots, even as with another human, is growing. Organic Human-Robot Interaction (O-HRI) is a general framework that includes expectations for robots in the form of scientific principles so that even non-robot specialists feel natural and stress-free when communicating with robots. This special journal issue focuses on the multidisciplinary field related to O-HRI, including robotics, cognitive science, psychology, and human-computer interaction. The articles in this issue deal with topics such as social robotics, emotion recognition, machine learning, and the ethical aspects of designing humanoid robots. By synthesizing diverse perspectives and cutting-edge research, this collection seeks to understand how O-HRI can improve user experience, strengthen trust and cooperation between humans and robots, and shape the future of human-robot coexistence.