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Fast Weight Attention

Project description

Fast Weight Attention (wip)

An attention based fast weight episodic memory, in the same vein as the memory MLP from TTT / Titans and fwPKM from Sakana AI

Citations

@article{zhang2026loger,
    title   = {LoGeR: Long-Context Geometric Reconstruction with Hybrid Memory},
    author  = {Zhang, Junyi and Herrmann, Charles and Hur, Junhwa and Sun, Chen and Yang, Ming-Hsuan and Cole, Forrester and Darrell, Trevor and Sun, Deqing},
    journal = {arXiv preprint arXiv:2603.03269},
    year    = {2026}
}
@misc{zhao2026fastweightproductkeymemory,
    title   = {Fast-weight Product Key Memory},
    author  = {Tianyu Zhao and Llion Jones},
    year    = {2026},
    eprint  = {2601.00671},
    archivePrefix = {arXiv},
    primaryClass = {cs.CL},
    url     = {https://arxiv.org/abs/2601.00671},
}
@misc{jordan2024muon,
    author       = {Keller Jordan and Yuchen Jin and Vlado Boza and Jiacheng You and Franz Cesista and Laker Newhouse and Jeremy Bernstein},
    title        = {Muon: An optimizer for hidden layers in neural networks},
    year         = {2024},
    url          = {https://kellerjordan.github.io/posts/muon/}
}

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