← All works
Adaptive depth

Adaptive Loops and Memory

Adaptive Loops and Memory in Transformers: Think Harder or Know More?

Markus Frey, Behzad Shomali, Ali Hamza Bashir, David Berghaus, Joachim Koehler, Mehdi Ali

Combines adaptive per-layer looping, where each block learns to iterate with a halting mechanism, with gated memory banks that add learned storage, to test whether models should think harder or know more.

Inside the method

Layer ℓ: [ Block ] × rℓ (halting) + gated memory bank

Simplified conceptual schematic. Consult the paper for the complete architecture.

Recurrence family
Adaptive depth
Depth control
Per-layer learned halting
KV / state strategy
Gated memory banks

Reading note

Looping mainly helps math while memory recovers commonsense performance; together they beat an iso-FLOP baseline with three times as many layers on math. Early layers loop little and later layers loop and read memory more.

Sources checked 2026-10-28. This catalog does not imply independent reproduction.

Related works

Cite this work

@misc{adaptiveloopsmemory2026,
  title = {Adaptive Loops and Memory in Transformers: Think Harder or Know More?},
  author = {Markus Frey and Behzad Shomali and Ali Hamza Bashir and David Berghaus and Joachim Koehler and Mehdi Ali},
  year = {2026},
  eprint = {2603.08391},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.08391}
}

Suggest a correction on GitHub ↗