A General Theoretical Framework for Learning Smallest Interpretable Models

Ordyniak, Sebastian; Paesani, Giacomo; Rychlicki, Mateusz; Szeider, Stefan

doi:10.1016/J.ARTINT.2025.104441

by Sebastian Ordyniak, Giacomo Paesani, Mateusz Rychlicki, Stefan Szeider

Reference:

A General Theoretical Framework for Learning Smallest Interpretable ModelsSebastian Ordyniak, Giacomo Paesani, Mateusz Rychlicki, Stefan SzeiderArtificial Intelligence, volume 350, pages 104441, 2026.

Bibtex Entry:

@string{ai="Artificial Intelligence"}
@article{OrdyniakPRS26,
  author       = {Sebastian Ordyniak and
                  Giacomo Paesani and
                  Mateusz Rychlicki and
                  Stefan Szeider},
  title        = {A General Theoretical Framework for Learning Smallest Interpretable
                  Models},
  journal      = AI,
  volume       = {350},
  pages        = {104441},
  year         = {2026},
  url          = {https://doi.org/10.1016/j.artint.2025.104441},
  doi          = {10.1016/J.ARTINT.2025.104441},
  keywords    ={asksat, strides, reveal},
}