James Hinns

According to our database, James Hinns authored at least 9 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2026

On the Definition and Detection of Cherry-Picking in Counterfactual Explanations.

James Hinns, Sofie Goethals, Stephan Van der Veeken, Theodoros Evgeniou, David Martens

CoRR, January, 2026

2025

Aggregating Local Saliency Maps for Semi-Global Explainable Image Classification.

James Hinns, David Martens

CoRR, June, 2025

Cash or Comfort? How LLMs Value Your Inconvenience.

Mateusz Cedro, Timour Ichmoukhamedov, Sofie Goethals, Yifan He, James Hinns, David Martens

CoRR, June, 2025

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

Exposing Shortcuts in Image Classification by Aggregating Counterfactuals.

James Hinns, David Martens

Proceedings of the Computational Intelligence - 17th International Joint Conference, 2025

2024

How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives.

Timour Ichmoukhamedov, James Hinns, David Martens

CoRR, 2024

Exposing Image Classifier Shortcuts with Counterfactual Frequency (CoF) Tables.

James Hinns, David Martens

CoRR, 2024

2023

Tell Me a Story! Narrative-Driven XAI with Large Language Models.

David Martens, Camille Dams, James Hinns, Mark Vergouwen

CoRR, 2023

2021

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, Veera Raghava Reddy Kovvuri, Mehmet Orcun Yalcin, Markus Roggenbach

Proceedings of the PRICAI 2021: Trends in Artificial Intelligence, 2021