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MIT Presents New Approach for Sequence-to-Sequence Learning with Latent Neural Grammars

Sequence to sequence modelling (seq2seq) with neural networks has become the de facto standard for sequence prediction tasks such as those found in language modelling and machine translation. The basic idea is to use an encoder to transform the input sequence into a context vector; then use a decoder to extract an output sequence that…

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