6 papers across 3 sessions
We present SynLogic: a data synthesis framework and logical reasoning dataset encompassing 35 tasks.
We propose Curriculum Abductive Learning (C-ABL), a method that explicitly leverages structural properties of domain knowledge bases to improve training efficiency, stability and reasoning accuracy in ABL.
We mechanistically analyze how large language models solve synthetic propositional logic problems.