AI RESEARCH
Fast weight programming and linear transformers: from machine learning to neurobiology
arXiv CS.LG
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ArXi:2508.08435v5 Announce Type: replace Recent advances in artificial neural networks for machine learning, and language modeling in particular, have established a family of recurrent neural network (RNN) architectures that, unlike conventional RNNs with vector-form hidden states, use two-dimensional (2D) matrix-form hidden states.