4 citations · 5 across the 4 of their papers we have counts for
4 papers
On the Definition and Detection of Cherry-Picking in Counterfactual Explanations
James Hinns, Sofie Goethals, Stephan Van der Veeken +2
Counterfactual explanations are widely used to communicate how inputs must change for a model to alter its prediction. For a single instance, many valid counterfactuals can exist,…
Beware of "Explanations" of AI
David Martens, Galit Shmueli, Theodoros Evgeniou +14
Understanding the decisions made and actions taken by increasingly complex AI system remains a key challenge. This has led to an expanding field of research in explainable artifici…
Evaluation and Facilitation of Online Discussions in the LLM Era: A Survey
Katerina Korre, Dimitris Tsirmpas, Nikos Gkoumas +5
We present a survey of methods for assessing and enhancing the quality of online discussions, focusing on the potential of LLMs. While online discourses aim, at least in theory, to…
Tell Me a Story! Narrative-Driven XAI with Large Language Models
David Martens, James Hinns, Camille Dams +2
In many AI applications today, the predominance of black-box machine learning models, due to their typically higher accuracy, amplifies the need for Explainable AI (XAI). Existing…