Storing Is Not Remembering: LSTM-UT and Bounded Gated Memory for Looped Transformers
Recurrent-depth Transformers reuse one block across many steps, so information needed later must survive repeated rewriting of the hidden state. A natural remedy is to keep more history. We show that, in controlled cellular-automaton tasks, making history available is not the same as making it usable. Using Rule 30, where the correct state is known at every recurrent step, we test depth extrapolation and de- layed recall, the recovery of an earlier state after further computation. CoTFormer, which caches keys and values from every earlier step, extrapolates less far and recalls less accurately than a Block Universal Transformer (BUT) that keeps only its current state. Interventions show t...
| Authors | Aras Kavuncu, Muhammad Burhan Hafez |
|---|---|
| Primary category | cs.LG |
| Published | 17 September 2026 |
| Last updated at source | 5 October 2026 |
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.