DRAGNN: A Transition-based Framework for Dynamically Connected Neural Networks

13 Mar 2017Lingpeng KongChris AlbertiDaniel AndorIvan BogatyyDavid Weiss

In this work, we present a compact, modular framework for constructing novel recurrent neural architectures. Our basic module is a new generic unit, the Transition Based Recurrent Unit (TBRU)... (read more)

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