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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 7 of 7 1 A Strong Baseline for Learning Cross-Lingual Word Embeddings from Sentence Alignments ... Levy, Omer; Søgaard, Anders; Goldberg, Yoav. - : arXiv, 2016 BASE Show details 2 Universal Dependencies 1.4 Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2016 BASE Show details 3 Universal Dependencies 1.3 Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2016 BASE Show details 4 Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks ... Adi, Yossi; Kermany, Einat; Belinkov, Yonatan; Lavi, Ofer; Goldberg, Yoav. - : arXiv, 2016 Abstract: There is a lot of research interest in encoding variable length sentences into fixed length vectors, in a way that preserves the sentence meanings. Two common methods include representations based on averaging word vectors, and representations based on the hidden states of recurrent neural networks such as LSTMs. The sentence vectors are used as features for subsequent machine learning tasks or for pre-training in the context of deep learning. However, not much is known about the properties that are encoded in these sentence representations and about the language information they capture. We propose a framework that facilitates better understanding of the encoded representations. We define prediction tasks around isolated aspects of sentence structure (namely sentence length, word content, and word order), and score representations by the ability to train a classifier to solve each prediction task when using the representation as input. We demonstrate the potential contribution of the approach by analyzing ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/1608.04207 https://dx.doi.org/10.48550/arxiv.1608.04207 BASE Hide details 5 Multilingual Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Models and Auxiliary Loss ... Plank, Barbara; Søgaard, Anders; Goldberg, Yoav. - : arXiv, 2016 BASE Show details 6 Semi Supervised Preposition-Sense Disambiguation using Multilingual Data ... Gonen, Hila; Goldberg, Yoav. - : arXiv, 2016 BASE Show details 7 Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies ... Linzen, Tal; Dupoux, Emmanuel; Goldberg, Yoav. - : arXiv, 2016 BASE Show details

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