48 citations · 86 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 48 cited
Scaling Up Models and Data with and
Adam Roberts, Hyung Won Chung, Anselm Levskaya +40
Recent neural network-based language models have benefited greatly from scaling up the size of training datasets and the number of parameters in the models themselves. Scaling can…
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…