Accelerating NeurASP with vectorization and caching 事件

Accelerating NeurASP with vectorization and caching arXiv:2606.10787v1 Announce Type: new Abstract: Neurosymbolic AI combines neural networks with symbolic programs to create robust and explainable predictions. One such framework is NeurASP, which trains a neural network to predict concepts and reasons over them using rules written in answer set programming (ASP) to solve downstream tasks. Crucially, labels are only provided for the downstream prediction produced by the symbolic rules, not for