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Recurrent Transformer (wip)

Explorations into the Recurrent Transformer proposed by Costin-Andrei Oncescu et al. of Harvard University

Citations

@misc{oncescu2026recurrenttransformergreatereffective,
    title   = {The Recurrent Transformer: Greater Effective Depth and Efficient Decoding},
    author  = {Costin-Andrei Oncescu and Depen Morwani and Samy Jelassi and Alexandru Meterez and Mujin Kwun and Sham Kakade},
    year    = {2026},
    eprint  = {2604.21215},
    archivePrefix = {arXiv},
    primaryClass = {cs.LG},
    url     = {https://arxiv.org/abs/2604.21215},
}

Release files for recurrent-transformer-pytorch 0.0.1

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Source distribution for recurrent-transformer-pytorch 0.0.1
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recurrent_transformer_pytorch-0.0.1-py3-none-any.whl Python 3 none any Details

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