Author

Giovanni Monea

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#artificial intelligence Preprint Oct 2026

The Surprising Effectiveness of Shared Memory in Looped Transformers

Looped Transformers apply the same layers several times per token, adding compute to improve quality without more parameters. Each recursion, however, writes its own key-value cache, so memory still grows with compute. Inference-time techniques can shrink this cache at a cost in quality. We pretrain looped language mod...

Giovanni Monea, Keshav Ramji, Yousef El-Kurdi et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Almost Free State Prediction Separation

This paper takes state--prediction separation to its limit with a free pause token: a prediction stream that writes no keys or values at all and so rides the sequence's existing positions, and reduces the raw flops required at inference time.

John Langford, Nathan Godey, Giovanni Monea et al. · 1 citation