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Pretraining Recurrent Networks without Recurrence

Akarsh Kumar, Phillip Isola
Jun 5, 2026 at 04:00
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arXiv:2606.06479v1 Announce Type: cross Abstract: Training recurrent neural networks (RNNs) requires assigning credit across long sequences of computations. Standard backpropagation through time (BPTT) addresses this problem poorly: it is sequential in time, limiting parallelism, and suffers from vanishing or exploding gradients, making...

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