Papers with SRNs

1 papers
How much complexity does an RNN architecture need to learn syntax-sensitive dependencies? (2020.acl-srw)

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Challenge: Long-term memory (LSTM) networks are capable of encapsulating long-range dependencies . but simple recurrent networks (SRNs) have been less successful at capturing long-term dependencies and loci of grammatical errors in an unsupervised setting.
Approach: They propose a new architecture that incorporates the decaying nature of neuronal activations and models the excitatory and inhibitory connections in a population of neurons.
Outcome: The proposed architecture shows competitive performance relative to LSTMs on subject-verb agreement, sentence grammaticality, and language modeling tasks.

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