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cs.AI2026
Distilling Answer-Set Programming Rules from LLMs for Neurosymbolic Visual Question Answering
Thomas Eiter, Nelson Higuera Ruiz, Johannes Oetsch
Visual Question Answering (VQA) is the task of answering questions about images, requiring the integration of multimodal input and reasoning. Modular approaches that incorporate lo…
cs.AI2026
Answer-Set-Programming-based Abstractions for Reinforcement Learning
Rafael Bankosegger, Thomas Eiter, Johannes Oetsch
Reinforcement Learning (RL) enables autonomous agents to learn policies from experience, but realistic problems often involve enormous state spaces, making learning and generalisat…
cs.AI2026
Visual Perceptual to Conceptual First-Order Rule Learning Networks
Kun Gao, Davide SoldÃ, Thomas Eiter +1
Learning rules plays a crucial role in deep learning, particularly in explainable artificial intelligence and enhancing the reasoning capabilities of large language models. While e…