40 citations · 131 across the 4 of their papers we have counts for
11 papers · 1 filter
Learning Cross-Context Entity Representations from Text
Jeffrey Ling, Nicholas FitzGerald, Zifei Shan +4
Language modeling tasks, in which words, or word-pieces, are predicted on the basis of a local context, have been very effective for learning word embeddings and context dependent…
A Fast, Compact, Accurate Model for Language Identification of Codemixed Text
Yuan Zhang, Jason Riesa, Daniel Gillick +3
We address fine-grained multilingual language identification: providing a language code for every token in a sentence, including codemixed text containing multiple languages. Such…
State-of-the-art Chinese Word Segmentation with Bi-LSTMs
Ji Ma, Kuzman Ganchev, David Weiss
A wide variety of neural-network architectures have been proposed for the task of Chinese word segmentation. Surprisingly, we find that a bidirectional LSTM model, when combined wi…
Adversarial Neural Networks for Cross-lingual Sequence Tagging
Heike Adel, Anton Bryl, David Weiss +1
We study cross-lingual sequence tagging with little or no labeled data in the target language. Adversarial training has previously been shown to be effective for training cross-lin…
Linguistically-Informed Self-Attention for Semantic Role Labeling
Emma Strubell, Patrick Verga, Daniel Andor +2
Current state-of-the-art semantic role labeling (SRL) uses a deep neural network with no explicit linguistic features. However, prior work has shown that gold syntax trees can dram…
Natural Language Processing with Small Feed-Forward Networks
Jan A. Botha, Emily Pitler, Ji Ma +5
We show that small and shallow feed-forward neural networks can achieve near state-of-the-art results on a range of unstructured and structured language processing tasks while bein…