[vc_row][vc_column][vc_column_text]<\/p>\n
[\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column][vc_column_text]<\/p>\n
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
\nimplement culture-specific, trustful,\u00a0credible, satisfactory and emotionally coloured human-machine interfaces and artificial agents.<\/p>\n
\uf0b7 Cross-cultural processing of social signals
\n\uf0b7 Linguistic and social interactional exchanges
\n\uf0b7 Social Robotics: analysis and applications
\n\uf0b7 Human behaviour: Analysis and understanding
\n\uf0b7 Linguistic sentiment analysis
\n\uf0b7 Changes in sentiment expressions
\n\uf0b7 Cognitive Economy
\n\uf0b7 Group behaviour, group cognition and cultural specificity
\n\uf0b7 Influence of context on perception, memory and decision making
\n\uf0b7 Cognitive systems for multimodal signal analysis
\n\uf0b7 Nonlinear processing of audio-video social signals
\n\uf0b7 Multimodal social signal processing
\n\uf0b7 Other\u2026..[\/vc_column_text][vc_column_text]<\/p>\n
Overview:<\/strong> 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\u2014up to millions of participants. This positions LLMs as a powerful new tool for social science, akin to how the microscope revolutionized biology.<\/p>\n Promise and Potential:<\/strong> Goals of This Section:<\/strong><\/p>\n Planned action:<\/strong> AI has great potential to revolutionise products, processes, and strategies, yet its advancement is hindered by the lack of trustworthiness of AI solutions. This session introduces the PEP AI concept through three groundbreaking methodologies: the Neural Mesh computational paradigm to enhance power and precision, mathematically provable evidence for the stability and performance of AI-driven control solutions, and techniques for linguistically interpretable and explainable AI decisions. In addition to theoretical foundations, proof-of-concept implementations in healthcare and considerations of technology acceptance and the EU AI Act will be presented.[\/vc_column_text][vc_column_text]<\/p>\n 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 \u2013 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.[\/vc_column_text][vc_column_text]<\/p>\n 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.[\/vc_column_text][\/vc_column][\/vc_row]<\/p>\n","protected":false},"excerpt":{"rendered":" [vc_row][vc_column][vc_column_text] The conference is open to Session and Track proposals. Please click HERE to submit your proposal. [\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column][vc_column_text] Track:\u00a0Linguistic and Behavioural Interaction Analysis in Empathic Systems Track Organizers: Anna Esposito (Universit\u00e0 Vanvitelli\/IIASS, Italy) Antonietta M. Esposito (Osservatorio Vesuviano, Sezione di Napoli,Italy) Maria Koutsombogera (Trinity College Dublin, Ireland) Gennaro Cordasco (Universit\u00e0 Vanvitelli\/IIASS, Italy), Mauro Maldonato (Universit\u00e0 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"class_list":["post-30","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/scitope.com\/coginfocom25\/index.php?rest_route=\/wp\/v2\/pages\/30","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/scitope.com\/coginfocom25\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/scitope.com\/coginfocom25\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/scitope.com\/coginfocom25\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/scitope.com\/coginfocom25\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=30"}],"version-history":[{"count":38,"href":"https:\/\/scitope.com\/coginfocom25\/index.php?rest_route=\/wp\/v2\/pages\/30\/revisions"}],"predecessor-version":[{"id":924,"href":"https:\/\/scitope.com\/coginfocom25\/index.php?rest_route=\/wp\/v2\/pages\/30\/revisions\/924"}],"wp:attachment":[{"href":"https:\/\/scitope.com\/coginfocom25\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=30"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\nThe 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:\u00a0social simulation using LLMs<\/strong>.<\/p>\n
\nSocial simulation with LLMs offers groundbreaking opportunities, including:<\/p>\n\n
\n
\nGiven 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.[\/vc_column_text][vc_column_text]<\/p>\nTrack: AI NEXT<\/strong><\/h5>\n
Track Organisers:
\n\u00c1d\u00e1m Csap\u00f3 (Corvinus University of Budapest, Hungary)
\nAnna Sud\u00e1r\u00a0 (Corvinus University of Budapest, Hungary)
\nMarianna Eisenberg-Nagy\u00a0 (Corvinus University of Budapest, Hungary)<\/h6>\nScope:<\/h6>\n
Session: Virtual Reality<\/strong><\/h5>\n
Track Organizers:
\nIldik\u00f3 Horv\u00e1th & Anna Sud\u00e1r (Corvinus University of Budapest, Hungary)<\/h6>\nScope:<\/h6>\n
Track: Organic human-robot interaction for Social robotics<\/strong><\/h5>\n
Track Organizers:
\nCsilla Csukonyi (psychologist), University of Debrecen
\nNiitsuma Mihoko (etho-roboticist), Chuo University
\nAlmusawi Husam Abdulkareem (robot specialist) University of Debrecen<\/h6>\nScope:<\/h6>\n