4 papers
The Dual Role of Abstracting over the Irrelevant in Symbolic Explanations: Cognitive Effort vs. Understanding
Zeynep G. Saribatur, Johannes Langer, Ute Schmid
Explanations are central to human cognition, yet AI systems often produce outputs that are difficult to understand. While symbolic AI offers a transparent foundation for interpreta…
LLM-Generated Explanations Do Not Suffice for Ultra-Strong Machine Learning
Lun Ai, Johannes Langer, Ute Schmid +1
Ultra Strong Machine Learning (USML) refers to symbolic learning systems that not only improve their own performance but can also teach their acquired knowledge to quantifiably imp…
Aligning Generalisation Between Humans and Machines
Filip Ilievski, Barbara Hammer, Frank van Harmelen +22
Recent advances in AI -- including generative approaches -- have resulted in technology that can support humans in scientific discovery and forming decisions, but may also disrupt…
Can humans teach machines to code?
Céline Hocquette, Johannes Langer, Andrew Cropper +1
The goal of inductive program synthesis is for a machine to automatically generate a program from user-supplied examples. A key underlying assumption is that humans can provide suf…