arxiv
PublishedSeptember 18, 2026 at 4:00 AM
Small Enough to Know Everything: The Fully-Enumerable Transformer as an Instrument for the Science of Delayed Generalization
Publisher summary· verbatim
arXiv:2609.20166v1 Announce Type: new Abstract: Tiny transformers trained on fully-enumerable tasks occupy an unusual position in the study of grokking: every input can be evaluated, every generalization ceiling can be computed exactly, and hundreds of seeds cost minutes. We argue this regime is a s
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivSEA-LION-v4.8: A Technical Report12harxivMeasurement Under Selection: Decoy-Calibrated Failure Audits for Language Models12harxivLearning Submanifolds for Subsequent Inference on Random Dot Product Graphs, Part 1: Theory12harxivEvaluating Out-of-Distribution Robustness in Graph-Based Android Malware Classification: A New Principled Benchmark12hThe Bubble Brief
WEEKLYRead AI insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗