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arXiv Machine Learning By Benjamin L. Badger

Structured Recurrent Mixers for Massively Parallelized Sequence Generation

Read the original on arXiv Machine Learning →

arXiv:2605. 08696v4 Announce Type: replace-cross Abstract: Over the last two decades, language modeling has experienced a shift from the use of predominantly recurrent architectures that process tokens sequentially during training and inference to non-recurrent models that process sequence elements in parallel during training, which results in greater training efficiency and stability at the expense of lower inference throughput.

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