5 citations · 17 across the 14 of their papers we have counts for
14 papers
Multimodal Gender Fairness in Depression Prediction: Insights on Data from the USA & China
Joseph Cameron, Jiaee Cheong, Micol Spitale +1
Social agents and robots are increasingly being used in wellbeing settings. However, a key challenge is that these agents and robots typically rely on machine learning (ML) algorit…
ERR@HRI 2024 Challenge: Multimodal Detection of Errors and Failures in Human-Robot Interactions
Micol Spitale, Maria Teresa Parreira, Maia Stiber +7
Despite the recent advancements in robotics and machine learning (ML), the deployment of autonomous robots in our everyday lives is still an open challenge. This is due to multiple…
LEXI: Large Language Models Experimentation Interface
Guy Laban, Tomer Laban, Hatice Gunes
The recent developments in Large Language Models (LLM), mark a significant moment in the research and development of social interactions with artificial agents. These agents are wi…
Small but Fair! Fairness for Multimodal Human-Human and Robot-Human Mental Wellbeing Coaching
Jiaee Cheong, Micol Spitale, Hatice Gunes
In recent years, the affective computing (AC) and human-robot interaction (HRI) research communities have put fairness at the centre of their research agenda. However, none of the…
Graph in Graph Neural Network
Jiongshu Wang, Jing Yang, Jiankang Deng +2
Existing Graph Neural Networks (GNNs) are limited to process graphs each of whose vertices is represented by a vector or a single value, limited their representing capability to de…
Underneath the Numbers: Quantitative and Qualitative Gender Fairness in LLMs for Depression Prediction
Micol Spitale, Jiaee Cheong, Hatice Gunes
Recent studies show bias in many machine learning models for depression detection, but bias in LLMs for this task remains unexplored. This work presents the first attempt to invest…