Grokking From Abstraction to Intelligence

arXiv:2606.13753v1 Announce Type: cross Abstract: Grokking is the delayed onset of generalization in neural networks, arising long after they fit the training data. Whether the

arXiv:2607.06639v1 Announce Type: cross Abstract: On modular arithmetic, a network's embedding keeps compressing for tens of thousands of steps after it has already generalized.

arXiv:2603.29735v1 Announce Type: new Abstract: The evolution of intelligence in artificial systems provides a unique opportunity to identify universal computational principles.

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1wjnr7d/260711666_how_to_tame_grokking_representation/"> <img alt="[2607.11666] How to Tame Grokking:

arXiv:2607.06628v1 Announce Type: cross Abstract: Which properties of a partially trained network are causally portable to a different, independently trained network?

arXiv:2607.18433v1 Announce Type: cross Abstract: Intelligence appears under different names in different fields: as data compression in statistics and machine learning, as

<!-- SC_OFF --><div class="md"><p>I've been applying the Fiedler value (second-smallest eigenvalue of the weight graph Laplacian) combined with Scheffer critical slowing down