2 papers
cs.AI2026
The RAIL Principles for Neurosymbolic AI: Reasoning, Assurances, Interfacing and Learning
Agnese Chiatti, Michael Cochez, Cristina Cornelio +14
Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention. They complement the data-intensive statistical approaches of neural n…
cs.LG2025
Grokking Explained: A Statistical Phenomenon
Breno W. Carvalho, Artur S. d'Avila Garcez, LuÃs C. Lamb +1
Grokking, or delayed generalization, is an intriguing learning phenomenon where test set loss decreases sharply only after a model's training set loss has converged. This challenge…