Cover Image

FAIR_XAI: Improving Multimodal Foundation Model Fairness via Explainability for Wellbeing Assessment

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chiang, Sophie, Brennan, Tom, Dogan, Fethiye Irmak, Cheong, Jiaee, Gunes, Hatice
Format:	Preprint
Published:	2026
Subjects:	Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Investigating Associational Biases in Inter-Model Communication of Large Generative Models
by: Dogan, Fethiye Irmak, et al.
Published: (2026)

FAIRWELL: Fair Multimodal Self-Supervised Learning for Wellbeing Prediction
by: Cheong, Jiaee, et al.
Published: (2025)

Small but Fair! Fairness for Multimodal Human-Human and Robot-Human Mental Wellbeing Coaching
by: Cheong, Jiaee, et al.
Published: (2024)

Multimodal Gender Fairness in Depression Prediction: Insights on Data from the USA & China
by: Cameron, Joseph, et al.
Published: (2024)

Designing Social Robots with Ethical, User-Adaptive Explainability in the Era of Foundation Models
by: Dogan, Fethiye Irmak, et al.
Published: (2026)

Feature Aggregation with Latent Generative Replay for Federated Continual Learning of Socially Appropriate Robot Behaviours
by: Churamani, Nikhil, et al.
Published: (2024)

Who Owns The Robot?: Four Ethical and Socio-technical Questions about Wellbeing Robots in the Real World through Community Engagement
by: Axelsson, Minja, et al.
Published: (2025)

Reimagining Social Robots as Recommender Systems: Foundations, Framework, and Applications
by: Huang, Jin, et al.
Published: (2026)

Robot-Led Vision Language Model Wellbeing Assessment of Children
by: Abbasi, Nida Itrat, et al.
Published: (2025)

AsyReC: A Multimodal Graph-based Framework for Spatio-Temporal Asymmetric Dyadic Relationship Classification
by: Tang, Wang, et al.
Published: (2025)

Underneath the Numbers: Quantitative and Qualitative Gender Fairness in LLMs for Depression Prediction
by: Spitale, Micol, et al.
Published: (2024)

Exploring Causality for HRI: A Case Study on Robotic Mental Well-being Coaching
by: Spitale, Micol, et al.
Published: (2025)

U-Fair: Uncertainty-based Multimodal Multitask Learning for Fairer Depression Detection
by: Cheong, Jiaee, et al.
Published: (2025)

FG 2025 TrustFAA: the First Workshop on Towards Trustworthy Facial Affect Analysis: Advancing Insights of Fairness, Explainability, and Safety (TrustFAA)
by: Cheong, Jiaee, et al.
Published: (2025)

Automatic Depression Assessment using Machine Learning: A Comprehensive Survey
by: Song, Siyang, et al.
Published: (2025)

Do We Talk to Robots Like Therapists, and Do They Respond Accordingly? Language Alignment in AI Emotional Support
by: Chiang, Sophie, et al.
Published: (2025)

Uncertainty-based Fairness Measures
by: Kuzucu, Selim, et al.
Published: (2023)

GRACE: Generating Socially Appropriate Robot Actions Leveraging LLMs and Human Explanations
by: Dogan, Fethiye Irmak, et al.
Published: (2024)

Gender Fairness of Machine Learning Algorithms for Pain Detection
by: Green, Dylan, et al.
Published: (2025)

Machine Learning Fairness for Depression Detection using EEG Data
by: Kwok, Angus Man Ho, et al.
Published: (2025)

Social Robotics for Disabled Students: An Empirical Investigation of Embodiment, Roles and Interaction
by: Markelius, Alva, et al.
Published: (2025)

VirtualXAI: A User-Centric Framework for Explainability Assessment Leveraging GPT-Generated Personas
by: Makridis, Georgios, et al.
Published: (2025)

Beyond Vision: How Large Language Models Interpret Facial Expressions from Valence-Arousal Values
by: Mehra, Vaibhav, et al.
Published: (2025)

Technology-assisted Journal Writing for Improving Student Mental Wellbeing: Humanoid Robot vs. Voice Assistant
by: Sayis, Batuhan, et al.
Published: (2024)

Federated Learning of Socially Appropriate Agent Behaviours in Simulated Home Environments
by: Checker, Saksham, et al.
Published: (2024)

Explainable AI: A Combined XAI Framework for Explaining Brain Tumour Detection Models
by: McGonagle, Patrick, et al.
Published: (2026)

STREAK: Streaming Network for Continual Learning of Object Relocations under Household Context Drifts
by: Bartoli, Ermanno, et al.
Published: (2024)

XAI-Units: Benchmarking Explainability Methods with Unit Tests
by: Lee, Jun Rui, et al.
Published: (2025)

Explainability Through Human-Centric Design for XAI in Lung Cancer Detection
by: Rafferty, Amy, et al.
Published: (2025)

XAI-CLIP: ROI-Guided Perturbation Framework for Explainable Medical Image Segmentation in Multimodal Vision-Language Models
by: Alzubaidi, Thuraya, et al.
Published: (2026)

Rules or Weights? Comparing User Understanding of Explainable AI Techniques with the Cognitive XAI-Adaptive Model
by: Rawshan, Louth Bin, et al.
Published: (2026)

XAI for All: Can Large Language Models Simplify Explainable AI?
by: Mavrepis, Philip, et al.
Published: (2024)

XAI for In-hospital Mortality Prediction via Multimodal ICU Data
by: Li, Xingqiao, et al.
Published: (2023)

Seamful XAI: Operationalizing Seamful Design in Explainable AI
by: Ehsan, Upol, et al.
Published: (2022)

Explainable Generative AI (GenXAI): A Survey, Conceptualization, and Research Agenda
by: Schneider, Johannes
Published: (2024)

Explainable AI: XAI-Guided Context-Aware Data Augmentation
by: Mersha, Melkamu Abay, et al.
Published: (2025)

Explainable but Vulnerable: Adversarial Attacks on XAI Explanation in Cybersecurity Applications
by: Mia, Maraz, et al.
Published: (2025)

Assessing Model-Agnostic XAI Methods against EU AI Act Explainability Requirements
by: Sovrano, Francesco, et al.
Published: (2026)

Agentic Explainability at Scale: Between Corporate Fears and XAI Needs
by: Elsayed, Yomna, et al.
Published: (2026)

What People Share With a Robot When Feeling Lonely and Stressed and How It Helps Over Time
by: Laban, Guy, et al.
Published: (2025)