4 citations · 6 across the 7 of their papers we have counts for
3 papers · 1 filter
World Models in Artificial Intelligence: Sensing, Learning, and Reasoning Like a Child
Javier Del Ser, Jesus L. Lobo, Heimo Müller +1
World Models help Artificial Intelligence (AI) predict outcomes, reason about its environment, and guide decision-making. While widely used in reinforcement learning, they lack the…
Explaining and visualizing black-box models through counterfactual paths
Bastian Pfeifer, Mateusz Krzyzinski, Hubert Baniecki +3
Explainable AI (XAI) is an increasingly important area of machine learning research, which aims to make black-box models transparent and interpretable. In this paper, we propose a…
Ethical ChatGPT: Concerns, Challenges, and Commandments
Jianlong Zhou, Heimo Müller, Andreas Holzinger +1
Large language models, e.g. ChatGPT are currently contributing enormously to make artificial intelligence even more popular, especially among the general population. However, such…