A Study on Counterfactual Explanations: Investigating the impact of inter-class distance and data imbalance

Supporting non-expert users in modelling and understanding AI, an interactive CP approach: Bringing the power of advanced optimisation in employee scheduling to small and medium-sized organisations

Explainable artificial intelligence for intrusion detection in IoT networks: A deep learning based approach

Maxplain – Value-based Evaluation of Explainable AI Techniques

Machine learning algorithm to estimate cardiac output based on non-invasive arterial blood pressure measurements

How truthful explanation of a conceder negotiation agent affects human trust, compared to a neutral one

Negotiating task allocation in a team with the help of a negotiator agent

Evaluating Feature Attribution Methods: an Usecase on a Neural Fact-checking Model

SoK: Explainable Machine Learning for Computer Security Applications

Knowing About Knowing: An Illusion of Human Competence Can Hinder Appropriate Reliance on AI Systems

A General-Purpose Protocol for Multi-agent Based Explanations

A Human-In-the-Loop Framework to Assess Multimodal Machine Learning Models

Knowing Better Than the AI: How the Dunning-Kruger Effect Shapes Reliance on Human-AI Decision Making

Explainable Artificial Intelligence (XAI) Techniques - A Review and Case Study

Model-Agnostic XAI Models: Benefits, Limitations and Research Directions

Investigation of the evaluation techniques and tools used for model-specific XAI models

Tailoring User-Aware Agent Explanations to Properly Align Human Trust

Domain-Knowledge-Driven Explainable Product Quality Prediction: Using prior knowledge to improve explanations of quality prediction models

Interpretability and performance of surrogate decision trees produced by Viper

The perils and pitfalls of explainable AI: Strategies for explaining algorithmic decision-making