14 citations · 24 across the 27 of their papers we have counts for
32 papers
Hierarchical Multimodal Interaction Reasoning for Dyadic Relationship Recognition
Wang Tang, Fethiye Irmak Dogan, Linbo Qing +2
Dyadic relationship recognition aims to identify the latent social relationship between two individuals from their multimodal interactions. Existing methods typically project heter…
A Benchmark for Spatially Grounded Gesture Generation
Anna Deichler, Rishabh Dabral, Fethiye Irmak Dogan +2
Communication in shared space interweaves verbal and non-verbal signals, and pointing gestures anchor language to the environment: "put the cup on that one" is uninterpretable with…
HiBRIDGE: A Hierarchical Bayesian Neural Network Framework for Interpretable Dialogue Management in Group-Robot Interaction
Massimiliano Nigro, Hatice Gunes, Micol Spitale +1
In multi-party human-robot interaction, a robot must continuously decide whom to address and what to say to participate effectively in the conversation. In real-world interactions,…
Benevolent Bias in Multi-Turn Human-Agent Dialogue
Qianqi Liu, Jin Huang, Fethiye Irmak Dogan +1
Bias in human-agent interaction can manifest not only through hostile language but also as benevolent bias, whereby unequal treatment hides behind a warm, positive tone. To make it…
Why did My Robot Just Change Personality? Prompting Guidelines for a Grounded Robot Persona in LLM-Based HRI
Ashita Ashok, Franziska Babel, Patrick Holthaus +7
Large language models (LLMs) are increasingly used for verbal interaction in social robots, yet prompt design in human-robot interaction (HRI) remains underspecified. As a result,…
Evaluating Human and LLM-Generated Thematic Analysis in HRI for Vulnerable Populations: A Comparative and Ethical Analysis
Alva Markelius, Fethiye Irmak Dogan, Julie Bailey +1
Thematic analysis (TA) has long been regarded as an inherently human, reflexive, and interpretive process. However, the extent to which LLM-generated TA is appropriate for Human-Ro…
Mind the Context: Continual Learning of Socially Appropriate Robot Actions via Environmental-Social Disentanglement
Rafal Robert Karpinski, Fethiye Irmak Dogan, Nikhil Churamani +4
Social robots are expected to operate across diverse environments, where similar arrangements can imply different socially appropriate actions, e.g., starting a conversation may be…
Designing Social Robots for Inclusive Child Wellbeing Assessment: Insights from Communities Supporting Developmental Language Disorder and Forced Migration
Fethiye Irmak Dogan, Yue Lou, Alva Markelius +7
Assessing children's wellbeing and mental health can be particularly challenging for children experiencing communication barriers, such as children with Developmental Language Diso…
StARS: Socially Appropriate Robot Actions via a Recommender System-Driven Approach
Erencem Ozbey, Fethiye Irmak Dogan, Jin Huang +1
Social appropriateness in human-robot interaction (HRI) is not universal: different people can judge the same robot action differently in the same situation. To capture this inter-…
Toward Personalized Social Robots for Child Well-being: Data Requirement Principles from a Recommender-System Perspective
Jin Huang, Eric Nichols, Fethiye Irmak Dogan +1
Social robots are increasingly deployed in clinical settings to support the well-being of children, where effective support must be personalized to each child. Personalization, cho…
MM-Conv: A Multimodal Dataset and Benchmark for Context-Aware Grounding in 3D Dialogue
Anna Deichler, Jim O'Regan, Fethiye Irmak Dogan +4
Grounding language in the physical world requires AI systems to interpret references that emerge dynamically during conversation. While current vision-language models (VLMs) excel…
FAIR_XAI: Improving Multimodal Foundation Model Fairness via Explainability for Wellbeing Assessment
Sophie Chiang, Tom Brennan, Fethiye Irmak Dogan +2
In recent years, the integration of multimodal machine learning in wellbeing assessment has offered transformative potential for monitoring mental health. However, with the rapid a…
Designing Social Robots with Ethical, User-Adaptive Explainability in the Era of Foundation Models
Fethiye Irmak Dogan, Alva Markelius, Hatice Gunes
Foundation models are increasingly embedded in social robots, mediating not only what they say and do but also how they adapt to users over time. This shift renders traditional ``o…
Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directions
Saleh Afroogh, Syed Ishtiaque Ahmed, Petra Ahrweiler +46
This study provides a cross-disciplinary examination of Explainable Artificial Intelligence (XAI) approaches-focusing on deep neural networks (DNNs) and large language models (LLMs…
Investigating Associational Biases in Inter-Model Communication of Large Generative Models
Fethiye Irmak Dogan, Yuval Weiss, Kajal Patel +2
Social bias in generative AI can manifest not only as performance disparities but also as associational bias, whereby models learn and reproduce stereotypical associations between…
Reimagining Social Robots as Recommender Systems: Foundations, Framework, and Applications
Jin Huang, Fethiye Irmak Doğan, Hatice Gunes
Personalization in social robots refers to the ability of the robot to meet the needs and/or preferences of an individual user. Existing approaches typically rely on large language…
Social Robotics for Disabled Students: An Empirical Investigation of Embodiment, Roles and Interaction
Alva Markelius, Fethiye Irmak Doğan, Julie Bailey +3
Institutional and social barriers in higher education often prevent students with disabilities from effectively accessing support, including lengthy procedures, insufficient inform…
Expectations, Explanations, and Embodiment: Attempts at Robot Failure Recovery
Elmira Yadollahi, Fethiye Irmak Dogan, Yujing Zhang +4
Expectations critically shape how people form judgments about robots, influencing whether they view failures as minor technical glitches or deal-breaking flaws. This work explores…
AsyReC: A Multimodal Graph-based Framework for Spatio-Temporal Asymmetric Dyadic Relationship Classification
Wang Tang, Fethiye Irmak Dogan, Linbo Qing +1
Dyadic social relationships, which refer to relationships between two individuals who know each other through repeated interactions (or not), are shaped by shared spatial and tempo…
BT-ACTION: A Test-Driven Approach for Modular Understanding of User Instruction Leveraging Behaviour Trees and LLMs
Alexander Leszczynski, Sarah Gillet, Iolanda Leite +1
Natural language instructions are often abstract and complex, requiring robots to execute multiple subtasks even for seemingly simple queries. For example, when a user asks a robot…
Robot-Led Vision Language Model Wellbeing Assessment of Children
Nida Itrat Abbasi, Fethiye Irmak Dogan, Guy Laban +4
This study presents a novel robot-led approach to assessing children's mental wellbeing using a Vision Language Model (VLM). Inspired by the Child Apperception Test (CAT), the soci…
Let's move on: Topic Change in Robot-Facilitated Group Discussions
Georgios Hadjiantonis, Sarah Gillet, Marynel Vázquez +2
Robot-moderated group discussions have the potential to facilitate engaging and productive interactions among human participants. Previous work on topic management in conversationa…
STREAK: Streaming Network for Continual Learning of Object Relocations under Household Context Drifts
Ermanno Bartoli, Fethiye Irmak Dogan, Iolanda Leite
In real-world settings, robots are expected to assist humans across diverse tasks and still continuously adapt to dynamic changes over time. For example, in domestic environments,…
A Model-Agnostic Approach for Semantically Driven Disambiguation in Human-Robot Interaction
Fethiye Irmak Dogan, Maithili Patel, Weiyu Liu +2
Ambiguities are inevitable in human-robot interaction, especially when a robot follows user instructions in a large, shared space. For example, if a user asks the robot to find an…