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Amr Hegazy

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#machine learning Preprint Aug 2026

Gated Recurrent Transformers: Expressive Depth through Recurrent Modulation

Scaling transformer language models creates an inherent tension between expressivity and memory efficiency. While unique weights across layers preserve functional specialization---from input-grounding to abstract refinement---they incur a substantial memory footprint. Conversely, standard depth-sharing enforces uniform...

Amr Hegazy, Amr Alanwar, Mostafa Elhoushi · 2 citations

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