An Initial Study of Machine Learning Underspecification Using Feature Attribution Explainable AI Algorithms: A COVID-19 Virus Transmission Case Study. - James Hinns; Xiuyi Fan; Siyuan Liu 003; Veera Raghava Reddy Kovvuri; Mehmet Orcun Yalcin; Markus Roggenbach (PRICAI (1), 2021)

Tell Me a Story! Narrative-Driven XAI with Large Language Models. - David Martens; Camille Dams; James Hinns; Mark Vergouwen (CoRR, 2023)

Exposing Image Classifier Shortcuts with Counterfactual Frequency (CoF) Tables. - James Hinns; David Martens (CoRR, 2024)

How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives. - Timour Ichmoukhamedov; James Hinns; David Martens (CoRR, 2024)

Tell me a story! Narrative-driven XAI with Large Language Models. - David Martens; James Hinns; Camille Dams; Mark Vergouwen; Theodoros Evgeniou (Decis. Support Syst., 2025)

Cash or Comfort? How LLMs Value Your Inconvenience. - Mateusz Cedro; Timour Ichmoukhamedov; Sofie Goethals; Yifan He; James Hinns; David Martens (CoRR, 2025)

Aggregating Local Saliency Maps for Semi-Global Explainable Image Classification. - James Hinns; David Martens (CoRR, 2025)