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Reservoir Transformers (2012.15045v2)
Published 30 Dec 2020 in cs.CL
Abstract: We demonstrate that transformers obtain impressive performance even when some of the layers are randomly initialized and never updated. Inspired by old and well-established ideas in machine learning, we explore a variety of non-linear "reservoir" layers interspersed with regular transformer layers, and show improvements in wall-clock compute time until convergence, as well as overall performance, on various machine translation and (masked) LLMling tasks.
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