Globally Normalized Transition-Based Neural Networks
This paper describes the models behind SyntaxNet.
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- 2026-10-10
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SyntaxNet - Google's syntactic parser - A TensorFlow dependency library github.com
A TensorFlow implementation of the models described in Globally Normalized Transition-Based Neural Networks, Andor et al. (2016)
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Announcing SyntaxNet: The World’s Most Accurate Parser Goes Open Source googleresearch.blogspot.com
Release of SyntaxNet, "an open-source neural network framework implemented in TensorFlow that provides a foundation for Natural Language Understanding systems.
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Colors in Context: A Pragmatic Neural Model for Grounded Language Understanding transacl.org
Transactions of the Association for Computational Linguistics, 2017. [All Versions].
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Self-Normalizing Neural Networks arxiv.org
Appearance of the incredible SELU activation function.
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Announcing SyntaxNet: The World’s Most Accurate Parser Goes Open Source research.googleblog.com
Parsey McParseface's birth, a neural syntax tree parser.
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Neural Machine Translation by Jointly Learning to Align and Translate arxiv.org
Attention mechanism for LSTMs! Mostly, figures and formulas and their explanations revealed to be useful to me. I gave a talk on that paper here.
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