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Moses: Open Source Toolkit for Statistical Machine Translation
We describe an open-source toolkit for statistical machine translation whose novel contributions are (a) support for linguistically motivated factors, (b) confusion network decoding, and (c)Expand
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Neural Architectures for Named Entity Recognition
Comunicacio presentada a la 2016 Conference of the North American Chapter of the Association for Computational Linguistics, celebrada a San Diego (CA, EUA) els dies 12 a 17 de juny 2016.
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Hierarchical Attention Networks for Document Classification
We propose a hierarchical attention network for document classification. Our model has two distinctive characteristics: (i) it has a hierarchical structure that mirrors the hierarchical structure ofExpand
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Improved Part-of-Speech Tagging for Online Conversational Text with Word Clusters
We consider the problem of part-of-speech tagging for informal, online conversational text. We systematically evaluate the use of large-scale unsupervised word clustering and new lexical features toExpand
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Relational inductive biases, deep learning, and graph networks
Artificial intelligence (AI) has undergone a renaissance recently, making major progress in key domains such as vision, language, control, and decision-making. This has been due, in part, to cheapExpand
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Transition-Based Dependency Parsing with Stack Long Short-Term Memory
This work was sponsored in part by the U. S. Army Research Laboratory and the U. S. Army Research Office/nunder contract/grant number W911NF-10-1-0533, and in part by NSF CAREER grantExpand
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Finding Function in Form: Compositional Character Models for Open Vocabulary Word Representation
We introduce a model for constructing vector representations of words by composing characters using bidirectional LSTMs. Relative to traditional word representation models that have independentExpand
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Recurrent Neural Network Grammars
We introduce recurrent neural network grammars, probabilistic models of sentences with explicit phrase structure. We explain efficient inference procedures that allow application to both parsing andExpand
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A Simple, Fast, and Effective Reparameterization of IBM Model 2
We present a simple log-linear reparameterization of IBM Model 2 that overcomes problems arising from Model 1’s strong assumptions and Model 2’s overparameterization. Efficient inference, likelihoodExpand
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A Discriminative Graph-Based Parser for the Abstract Meaning Representation
Abstract Meaning Representation (AMR) is a semantic formalism for which a grow- ing set of annotated examples is avail- able. We introduce the first approach to parse sentences into this representa-Expand
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