collaborators

5 papers

cs.AI2026

LLM Consumer Behavior Theory: Foundations of a Novel Research Field

Manon Reusens, Sofie Goethals, David Martens

Large language models (LLMs) are increasingly deployed as autonomous agents that make consumption decisions on behalf of users. This shift raises fundamental questions for consumer…

cs.AI2026

Would a Large Language Model Pay Extra for a View? Inferring Willingness to Pay from Subjective Choices

Manon Reusens, Sofie Goethals, Toon Calders +1

As Large Language Models (LLMs) are increasingly deployed in applications such as travel assistance and purchasing support, they are often required to make subjective choices on be…

cs.LG2026

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,…

stat.ML2025

From What Ifs to Insights: Counterfactuals in Causal Inference vs. Explainable AI

Galit Shmueli, David Martens, Jaewon Yoo +1

Counterfactuals play a pivotal role in the two distinct data science fields of causal inference (CI) and explainable artificial intelligence (XAI). While the core idea behind count…

cs.LG2025

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…