269 citations · 646 across the 18 of their papers we have counts for
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cs.CL2017★ 38 cited
SyntaxNet Models for the CoNLL 2017 Shared Task
Chris Alberti, Daniel Andor, Ivan Bogatyy +10
We describe a baseline dependency parsing system for the CoNLL2017 Shared Task. This system, which we call "ParseySaurus," uses the DRAGNN framework [Kong et al, 2017] to combine t…
cs.CL2017★ 31 cited
DRAGNN: A Transition-based Framework for Dynamically Connected Neural Networks
Lingpeng Kong, Chris Alberti, Daniel Andor +2
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…