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Improving Distributional Similarity with Lessons Learned from Word Embeddings
Omer Levy
|
Yoav Goldberg
|
Ido Dagan
|
Paper Details:
Year: 2015
Venue:
TACL |
Citations
URL
D-GloVe: A Feasible Least Squares Model for Estimating Word Embedding Densities
Shoaib Jameel
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Steven Schockaert
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Predicting human similarity judgments with distributional models: The value of word associations.
Simon De Deyne
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Amy Perfors
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Daniel J Navarro
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Improved Word Embeddings with Implicit Structure Information
Jie Shen
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Cong Liu
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Bad Company—Neighborhoods in Neural Embedding Spaces Considered Harmful
Johannes Hellrich
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Udo Hahn
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On the contribution of word embeddings to temporal relation classification
Paramita Mirza
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Sara Tonelli
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Inducing Bilingual Lexica From Non-Parallel Data With Earth Mover’s Distance Regularization
Meng Zhang
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Yang Liu
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Huanbo Luan
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Yiqun Liu
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Maosong Sun
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Word Embeddings, Analogies, and Machine Learning: Beyond king - man + woman = queen
Aleksandr Drozd
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Anna Gladkova
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Satoshi Matsuoka
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Enhancing General Sentiment Lexicons for Domain-Specific Use
Tim Kreutz
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Walter Daelemans
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Learning Sentiment Composition from Sentiment Lexicons
Orith Toledo-Ronen
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Roy Bar-Haim
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Alon Halfon
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Charles Jochim
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Amir Menczel
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Ranit Aharonov
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Noam Slonim
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Why does PairDiff work? - A Mathematical Analysis of Bilinear Relational Compositional Operators for Analogy Detection
Huda Hakami
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Kohei Hayashi
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Danushka Bollegala
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SeVeN: Augmenting Word Embeddings with Unsupervised Relation Vectors
Luis Espinosa-Anke
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Steven Schockaert
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What’s in Your Embedding, And How It Predicts Task Performance
Anna Rogers
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Shashwath Hosur Ananthakrishna
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Anna Rumshisky
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AnlamVer: Semantic Model Evaluation Dataset for Turkish - Word Similarity and Relatedness
Gökhan Ercan
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Olcay Taner Yıldız
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Authorless Topic Models: Biasing Models Away from Known Structure
Laure Thompson
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David Mimno
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JeSemE: Interleaving Semantics and Emotions in a Web Service for the Exploration of Language Change Phenomena
Johannes Hellrich
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Sven Buechel
|
Udo Hahn
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Transparent, Efficient, and Robust Word Embedding Access with WOMBAT
Mark-Christoph Müller
|
Michael Strube
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Evaluation methods for unsupervised word embeddings
Tobias Schnabel
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Igor Labutov
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David Mimno
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Thorsten Joachims
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Convolutional Sentence Kernel from Word Embeddings for Short Text Categorization
Jonghoon Kim
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François Rousseau
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Michalis Vazirgiannis
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Component-Enhanced Chinese Character Embeddings
Yanran Li
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Wenjie Li
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Fei Sun
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Sujian Li
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Sarcastic or Not: Word Embeddings to Predict the Literal or Sarcastic Meaning of Words
Debanjan Ghosh
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Weiwei Guo
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Smaranda Muresan
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A Generative Word Embedding Model and its Low Rank Positive Semidefinite Solution
Shaohua Li
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Jun Zhu
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Chunyan Miao
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Bayesian Optimization of Text Representations
Dani Yogatama
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Lingpeng Kong
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Noah A. Smith
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Topic Identification and Discovery on Text and Speech
Chandler May
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Francis Ferraro
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Alan McCree
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Jonathan Wintrode
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Daniel Garcia-Romero
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Benjamin Van Durme
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Semi-Supervised Learning of Sequence Models with Method of Moments
Zita Marinho
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André F. T. Martins
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Shay B. Cohen
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Noah A. Smith
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Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora
William L. Hamilton
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Kevin Clark
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Jure Leskovec
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Dan Jurafsky
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WordRank: Learning Word Embeddings via Robust Ranking
Shihao Ji
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Hyokun Yun
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Pinar Yanardag
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Shin Matsushima
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S. V. N. Vishwanathan
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The Effects of Data Size and Frequency Range on Distributional Semantic Models
Magnus Sahlgren
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Alessandro Lenci
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Improving Sparse Word Representations with Distributional Inference for Semantic Composition
Thomas Kober
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Julie Weeds
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Jeremy Reffin
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David Weir
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Ngram2vec: Learning Improved Word Representations from Ngram Co-occurrence Statistics
Zhe Zhao
|
Tao Liu
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Shen Li
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Bofang Li
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Xiaoyong Du
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Learning Chinese Word Representations From Glyphs Of Characters
Tzu-Ray Su
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Hung-Yi Lee
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Exploiting Morphological Regularities in Distributional Word Representations
Arihant Gupta
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Syed Sarfaraz Akhtar
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Avijit Vajpayee
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Arjit Srivastava
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Madan Gopal Jhanwar
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Manish Shrivastava
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Word Embeddings based on Fixed-Size Ordinally Forgetting Encoding
Joseph Sanu
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Mingbin Xu
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Hui Jiang
|
Quan Liu
|
Incremental Skip-gram Model with Negative Sampling
Nobuhiro Kaji
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Hayato Kobayashi
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Measuring Thematic Fit with Distributional Feature Overlap
Enrico Santus
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Emmanuele Chersoni
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Alessandro Lenci
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Philippe Blache
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Outta Control: Laws of Semantic Change and Inherent Biases in Word Representation Models
Haim Dubossarsky
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Daphna Weinshall
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Eitan Grossman
|
Cross-domain Semantic Parsing via Paraphrasing
Yu Su
|
Xifeng Yan
|
Exploring Vector Spaces for Semantic Relations
Kata Gábor
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Haïfa Zargayouna
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Isabelle Tellier
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Davide Buscaldi
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Thierry Charnois
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Distinguishing Japanese Non-standard Usages from Standard Ones
Tatsuya Aoki
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Ryohei Sasano
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Hiroya Takamura
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Manabu Okumura
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Investigating Different Syntactic Context Types and Context Representations for Learning Word Embeddings
Bofang Li
|
Tao Liu
|
Zhe Zhao
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Buzhou Tang
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Aleksandr Drozd
|
Anna Rogers
|
Xiaoyong Du
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The strange geometry of skip-gram with negative sampling
David Mimno
|
Laure Thompson
|
Why is unsupervised alignment of English embeddings from different algorithms so hard?
Mareike Hartmann
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Yova Kementchedjhieva
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Anders Søgaard
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Quantifying Context Overlap for Training Word Embeddings
Yimeng Zhuang
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Jinghui Xie
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Yinhe Zheng
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Xuan Zhu
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Streaming word similarity mining on the cheap
Olof Görnerup
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Daniel Gillblad
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Dynamic Meta-Embeddings for Improved Sentence Representations
Douwe Kiela
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Changhan Wang
|
Kyunghyun Cho
|
A Probabilistic Model for Joint Learning of Word Embeddings from Texts and Images
Melissa Ailem
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Bowen Zhang
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Aurelien Bellet
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Pascal Denis
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Fei Sha
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A Framework for Understanding the Role of Morphology in Universal Dependency Parsing
Mathieu Dehouck
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Pascal Denis
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Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representations
Aditi Chaudhary
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Chunting Zhou
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Lori Levin
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Graham Neubig
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David R. Mortensen
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Jaime Carbonell
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Learning Gender-Neutral Word Embeddings
Jieyu Zhao
|
Yichao Zhou
|
Zeyu Li
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Wei Wang
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Kai-Wei Chang
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Learning Compositionality Functions on Word Embeddings for Modelling Attribute Meaning in Adjective-Noun Phrases
Matthias Hartung
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Fabian Kaupmann
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Soufian Jebbara
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Philipp Cimiano
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Hypernyms under Siege: Linguistically-motivated Artillery for Hypernymy Detection
Vered Shwartz
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Enrico Santus
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Dominik Schlechtweg
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A Strong Baseline for Learning Cross-Lingual Word Embeddings from Sentence Alignments
Omer Levy
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Anders Søgaard
|
Yoav Goldberg
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Explaining and Generalizing Skip-Gram through Exponential Family Principal Component Analysis
Ryan Cotterell
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Adam Poliak
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Benjamin Van Durme
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Jason Eisner
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Cross-Lingual Syntactically Informed Distributed Word Representations
Ivan Vulić
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Bag of Tricks for Efficient Text Classification
Armand Joulin
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Edouard Grave
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Piotr Bojanowski
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Tomas Mikolov
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When a Red Herring in Not a Red Herring: Using Compositional Methods to Detect Non-Compositional Phrases
Julie Weeds
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Thomas Kober
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Jeremy Reffin
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David Weir
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Applying Multi-Sense Embeddings for German Verbs to Determine Semantic Relatedness and to Detect Non-Literal Language
Maximilian Köper
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Sabine Schulte im Walde
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Detecting spelling variants in non-standard texts
Fabian Barteld
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Literal or idiomatic? Identifying the reading of single occurrences of German multiword expressions using word embeddings
Rafael Ehren
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Geographical Evaluation of Word Embeddings
Michal Konkol
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Tomáš Brychcín
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Michal Nykl
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Tomáš Hercig
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Turning Distributional Thesauri into Word Vectors for Synonym Extraction and Expansion
Olivier Ferret
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Combining Lightly-Supervised Text Classification Models for Accurate Contextual Advertising
Yiping Jin
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Dittaya Wanvarie
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Phu Le
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Towards Lower Bounds on Number of Dimensions for Word Embeddings
Kevin Patel
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Pushpak Bhattacharyya
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Big Data Small Data, In Domain Out-of Domain, Known Word Unknown Word: The Impact of Word Representations on Sequence Labelling Tasks
Lizhen Qu
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Gabriela Ferraro
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Liyuan Zhou
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Weiwei Hou
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Nathan Schneider
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Timothy Baldwin
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Leveraging Eventive Information for Better Metaphor Detection and Classification
I-Hsuan Chen
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Yunfei Long
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Qin Lu
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Chu-Ren Huang
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Embedding Words and Senses Together via Joint Knowledge-Enhanced Training
Massimiliano Mancini
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Jose Camacho-Collados
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Ignacio Iacobacci
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Roberto Navigli
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Automatic Selection of Context Configurations for Improved Class-Specific Word Representations
Ivan Vulić
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Roy Schwartz
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Ari Rappoport
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Roi Reichart
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Anna Korhonen
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Resources to Examine the Quality of Word Embedding Models Trained on n-Gram Data
Ábel Elekes
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Adrian Englhardt
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Martin Schäler
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Klemens Böhm
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Bringing Order to Neural Word Embeddings with Embeddings Augmented by Random Permutations (EARP)
Trevor Cohen
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Dominic Widdows
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Word Embedding Evaluation and Combination
Sahar Ghannay
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Benoit Favre
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Yannick Estève
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Nathalie Camelin
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mwetoolkit+sem: Integrating Word Embeddings in the mwetoolkit for Semantic MWE Processing
Silvio Cordeiro
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Carlos Ramisch
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Aline Villavicencio
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Neural Embedding Language Models in Semantic Clustering of Web Search Results
Andrey Kutuzov
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Elizaveta Kuzmenko
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Evaluating Unsupervised Dutch Word Embeddings as a Linguistic Resource
Stéphan Tulkens
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Chris Emmery
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Walter Daelemans
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What a Nerd! Beating Students and Vector Cosine in the ESL and TOEFL Datasets
Enrico Santus
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Alessandro Lenci
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Tin-Shing Chiu
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Qin Lu
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Chu-Ren Huang
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Advances in Pre-Training Distributed Word Representations
Tomas Mikolov
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Edouard Grave
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Piotr Bojanowski
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Christian Puhrsch
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Armand Joulin
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A Corpus to Learn Refer-to-as Relations for Nominals
Wasi Ahmad
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Kai-Wei Chang
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Urdu Word Embeddings
Samar Haider
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Evaluation of Domain-specific Word Embeddings using Knowledge Resources
Farhad Nooralahzadeh
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Lilja Øvrelid
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Jan Tore Lønning
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Distributional Term Set Expansion
Amaru Cuba Gyllensten
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Magnus Sahlgren
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Semantic Relatedness of Wikipedia Concepts – Benchmark Data and a Working Solution
Liat Ein Dor
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Alon Halfon
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Yoav Kantor
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Ran Levy
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Yosi Mass
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Ruty Rinott
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Eyal Shnarch
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Noam Slonim
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The brWaC Corpus: A New Open Resource for Brazilian Portuguese
Jorge A. Wagner Filho
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Rodrigo Wilkens
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Marco Idiart
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Aline Villavicencio
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Distinguishing Literal and Non-Literal Usage of German Particle Verbs
Maximilian Köper
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Sabine Schulte im Walde
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Right-truncatable Neural Word Embeddings
Jun Suzuki
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Masaaki Nagata
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Learning Distributed Representations of Sentences from Unlabelled Data
Felix Hill
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Kyunghyun Cho
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Anna Korhonen
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Retrofitting Sense-Specific Word Vectors Using Parallel Text
Allyson Ettinger
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Philip Resnik
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Marine Carpuat
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Analogy-based detection of morphological and semantic relations with word embeddings: what works and what doesn’t.
Anna Gladkova
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Aleksandr Drozd
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Satoshi Matsuoka
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Can Network Embedding of Distributional Thesaurus Be Combined with Word Vectors for Better Representation?
Abhik Jana
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Pawan Goyal
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Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources
Ivan Vulić
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Goran Glavaš
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Nikola Mrkšić
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Anna Korhonen
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Unsupervised Learning of Sentence Embeddings Using Compositional n-Gram Features
Matteo Pagliardini
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Prakhar Gupta
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Martin Jaggi
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Querying Word Embeddings for Similarity and Relatedness
Fatemeh Torabi Asr
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Robert Zinkov
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Michael Jones
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Global Relation Embedding for Relation Extraction
Yu Su
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Honglei Liu
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Semih Yavuz
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Izzeddin Gür
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Huan Sun
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Xifeng Yan
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Learning Word Embeddings for Low-Resource Languages by PU Learning
Chao Jiang
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Hsiang-Fu Yu
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Cho-Jui Hsieh
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Kai-Wei Chang
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Word Emotion Induction for Multiple Languages as a Deep Multi-Task Learning Problem
Sven Buechel
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Udo Hahn
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Frustratingly Easy Meta-Embedding – Computing Meta-Embeddings by Averaging Source Word Embeddings
Joshua Coates
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Danushka Bollegala
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Document-based Recommender System for Job Postings using Dense Representations
Ahmed Elsafty
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Martin Riedl
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Chris Biemann
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Towards Qualitative Word Embeddings Evaluation: Measuring Neighbors Variation
Bénédicte Pierrejean
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Ludovic Tanguy
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Model-based Word Embeddings from Decompositions of Count Matrices
Karl Stratos
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Michael Collins
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Daniel Hsu
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A Unified Learning Framework of Skip-Grams and Global Vectors
Jun Suzuki
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Masaaki Nagata
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A Hierarchical Knowledge Representation for Expert Finding on Social Media
Yanran Li
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Wenjie Li
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Sujian Li
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Bilingual Word Embeddings from Non-Parallel Document-Aligned Data Applied to Bilingual Lexicon Induction
Ivan Vulić
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Marie-Francine Moens
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Low-Rank Tensors for Verbs in Compositional Distributional Semantics
Daniel Fried
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Tamara Polajnar
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Stephen Clark
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Intrinsic Subspace Evaluation of Word Embedding Representations
Yadollah Yaghoobzadeh
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Hinrich Schütze
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On the Role of Seed Lexicons in Learning Bilingual Word Embeddings
Ivan Vulić
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Anna Korhonen
|
Generative Topic Embedding: a Continuous Representation of Documents
Shaohua Li
|
Tat-Seng Chua
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Jun Zhu
|
Chunyan Miao
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Embeddings for Word Sense Disambiguation: An Evaluation Study
Ignacio Iacobacci
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Mohammad Taher Pilehvar
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Roberto Navigli
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Learning Semantically and Additively Compositional Distributional Representations
Ran Tian
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Naoaki Okazaki
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Kentaro Inui
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Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change
William L. Hamilton
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Jure Leskovec
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Dan Jurafsky
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Take and Took, Gaggle and Goose, Book and Read: Evaluating the Utility of Vector Differences for Lexical Relation Learning
Ekaterina Vylomova
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Laura Rimell
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Trevor Cohn
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Timothy Baldwin
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Predicting the Compositionality of Nominal Compounds: Giving Word Embeddings a Hard Time
Silvio Cordeiro
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Carlos Ramisch
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Marco Idiart
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Aline Villavicencio
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Jointly Learning to Embed and Predict with Multiple Languages
Daniel C. Ferreira
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André F. T. Martins
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Mariana S. C. Almeida
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Supersense Embeddings: A Unified Model for Supersense Interpretation, Prediction, and Utilization
Lucie Flekova
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Iryna Gurevych
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Word Embeddings with Limited Memory
Shaoshi Ling
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Yangqiu Song
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Dan Roth
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Matrix Factorization using Window Sampling and Negative Sampling for Improved Word Representations
Alexandre Salle
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Aline Villavicencio
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Marco Idiart
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Is “Universal Syntax” Universally Useful for Learning Distributed Word Representations?
Ivan Vulić
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Anna Korhonen
|
Nonparametric Spherical Topic Modeling with Word Embeddings
Kayhan Batmanghelich
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Ardavan Saeedi
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Karthik Narasimhan
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Sam Gershman
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Robust Co-occurrence Quantification for Lexical Distributional Semantics
Dmitrijs Milajevs
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Mehrnoosh Sadrzadeh
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Matthew Purver
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Deep Learning in Semantic Kernel Spaces
Danilo Croce
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Simone Filice
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Giuseppe Castellucci
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Roberto Basili
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Riemannian Optimization for Skip-Gram Negative Sampling
Alexander Fonarev
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Oleksii Grinchuk
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Gleb Gusev
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Pavel Serdyukov
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Ivan Oseledets
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Information-Theory Interpretation of the Skip-Gram Negative-Sampling Objective Function
Oren Melamud
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Jacob Goldberger
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Learning Topic-Sensitive Word Representations
Marzieh Fadaee
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Arianna Bisazza
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Christof Monz
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An Empirical Study on End-to-End Sentence Modelling
Kurt Junshean Espinosa
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Exploring Diachronic Lexical Semantics with JeSemE
Johannes Hellrich
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Udo Hahn
|
Explicit Retrofitting of Distributional Word Vectors
Goran Glavaš
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Ivan Vulić
|
Bridging Languages through Images with Deep Partial Canonical Correlation Analysis
Guy Rotman
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Ivan Vulić
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Roi Reichart
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Incorporating Latent Meanings of Morphological Compositions to Enhance Word Embeddings
Yang Xu
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Jiawei Liu
|
Wei Yang
|
Liusheng Huang
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SemAxis: A Lightweight Framework to Characterize Domain-Specific Word Semantics Beyond Sentiment
Jisun An
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Haewoon Kwak
|
Yong-Yeol Ahn
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A Rank-Based Similarity Metric for Word Embeddings
Enrico Santus
|
Hongmin Wang
|
Emmanuele Chersoni
|
Yue Zhang
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Word Embeddings as Metric Recovery in Semantic Spaces
Tatsunori B. Hashimoto
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David Alvarez-Melis
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Tommi S. Jaakkola
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Sparse Coding of Neural Word Embeddings for Multilingual Sequence Labeling
Gábor Berend
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Evaluating the Stability of Embedding-based Word Similarities
Maria Antoniak
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David Mimno
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Joint Unsupervised Learning of Semantic Representation of Words and Roles in Dependency Trees
Michal Konkol
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Quantificational features in distributional word representations
Tal Linzen
|
Emmanuel Dupoux
|
Benjamin Spector
|
Improving Zero-Shot-Learning for German Particle Verbs by using Training-Space Restrictions and Local Scaling
Maximilian Köper
|
Sabine Schulte im Walde
|
Max Kisselew
|
Sebastian Padó
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evision PDF of 'When Hyperparameters Help: Beneficial Parameter Combinations in Distributional Semantic Models
Alicia Krebs
|
Denis Paperno
|
Random Positive-Only Projections: PPMI-Enabled Incremental Semantic Space Construction
Behrang QasemiZadeh
|
Laura Kallmeyer
|
What Analogies Reveal about Word Vectors and their Compositionality
Gregory Finley
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Stephanie Farmer
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Serguei Pakhomov
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A Mixture Model for Learning Multi-Sense Word Embeddings
Dai Quoc Nguyen
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Dat Quoc Nguyen
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Ashutosh Modi
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Stefan Thater
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Manfred Pinkal
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HCCL at SemEval-2017 Task 2: Combining Multilingual Word Embeddings and Transliteration Model for Semantic Similarity
Junqing He
|
Long Wu
|
Xuemin Zhao
|
Yonghong Yan
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Jmp8 at SemEval-2017 Task 2: A simple and general distributional approach to estimate word similarity
Josué Melka
|
Gilles Bernard
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Meaning_space at SemEval-2018 Task 10: Combining explicitly encoded knowledge with information extracted from word embeddings
Pia Sommerauer
|
Antske Fokkens
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Piek Vossen
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Robust Handling of Polysemy via Sparse Representations
Abhijit Mahabal
|
Dan Roth
|
Sid Mittal
|
A Simple Word Embedding Model for Lexical Substitution
Oren Melamud
|
Omer Levy
|
Ido Dagan
|
Towards a Model of Prediction-based Syntactic Category Acquisition: First Steps with Word Embeddings
Robert Grimm
|
Giovanni Cassani
|
Walter Daelemans
|
Steven Gillis
|
Evaluating distributed word representations for capturing semantics of biomedical concepts
Muneeb TH
|
Sunil Sahu
|
Ashish Anand
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Unsupervised Modeling of Topical Relevance in L2 Learner Text
Ronan Cummins
|
Helen Yannakoudakis
|
Ted Briscoe
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Leveraging Data-Driven Methods in Word-Level Language Identification for a Multilingual Alpine Heritage Corpus
Ada Wan
|
A Joint Model for Word Embedding and Word Morphology
Kris Cao
|
Marek Rei
|
Towards cross-lingual distributed representations without parallel text trained with adversarial autoencoders
Antonio Valerio Miceli Barone
|
Towards Generalizable Sentence Embeddings
Eleni Triantafillou
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Jamie Ryan Kiros
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Raquel Urtasun
|
Richard Zemel
|
Intrinsic Evaluation of Word Vectors Fails to Predict Extrinsic Performance
Billy Chiu
|
Anna Korhonen
|
Sampo Pyysalo
|
Issues in evaluating semantic spaces using word analogies
Tal Linzen
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Evaluating Word Embeddings Using a Representative Suite of Practical Tasks
Neha Nayak
|
Gabor Angeli
|
Christopher D. Manning
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Problems With Evaluation of Word Embeddings Using Word Similarity Tasks
Manaal Faruqui
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Yulia Tsvetkov
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Pushpendre Rastogi
|
Chris Dyer
|
Intrinsic Evaluations of Word Embeddings: What Can We Do Better?
Anna Gladkova
|
Aleksandr Drozd
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Find the word that does not belong: A Framework for an Intrinsic Evaluation of Word Vector Representations
José Camacho-Collados
|
Roberto Navigli
|
Evaluation of acoustic word embeddings
Sahar Ghannay
|
Yannick Estève
|
Nathalie Camelin
|
Paul Deleglise
|
Evaluating word embeddings with fMRI and eye-tracking
Anders Søgaard
|
bot.zen @ EmpiriST 2015 - A minimally-deep learning PoS-tagger (trained for German CMC and Web data)
Egon Stemle
|
How to Train good Word Embeddings for Biomedical NLP
Billy Chiu
|
Gamal Crichton
|
Anna Korhonen
|
Sampo Pyysalo
|
Feelings from the Past—Adapting Affective Lexicons for Historical Emotion Analysis
Sven Buechel
|
Johannes Hellrich
|
Udo Hahn
|
Modifications of Machine Translation Evaluation Metrics by Using Word Embeddings
Haozhou Wang
|
Paola Merlo
|
Evaluation of distributional semantic models: a holistic approach
Gabriel Bernier-Colborne
|
Patrick Drouin
|
The CogALex-V Shared Task on the Corpus-Based Identification of Semantic Relations
Enrico Santus
|
Anna Gladkova
|
Stefan Evert
|
Alessandro Lenci
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CogALex-V Shared Task: GHHH - Detecting Semantic Relations via Word Embeddings
Mohammed Attia
|
Suraj Maharjan
|
Younes Samih
|
Laura Kallmeyer
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Thamar Solorio
|
CogALex-V Shared Task: ROOT18
Emmanuele Chersoni
|
Giulia Rambelli
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Enrico Santus
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Redefining Context Windows for Word Embedding Models: An Experimental Study
Pierre Lison
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Andrey Kutuzov
|
Complex Verbs are Different: Exploring the Visual Modality in Multi-Modal Models to Predict Compositionality
Maximilian Köper
|
Sabine Schulte im Walde
|
Context encoders as a simple but powerful extension of word2vec
Franziska Horn
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Knowledge Base Completion: Baselines Strike Back
Rudolf Kadlec
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Ondrej Bajgar
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Jan Kleindienst
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community2vec: Vector representations of online communities encode semantic relationships
Trevor Martin
|
Hypothesis Testing based Intrinsic Evaluation of Word Embeddings
Nishant Gurnani
|
The Sentimental Value of Chinese Sub-Character Components
Yassine Benajiba
|
Or Biran
|
Zhiliang Weng
|
Yong Zhang
|
Jin Sun
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Semantic Composition via Probabilistic Model Theory
Guy Emerson
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Ann Copestake
|
Network Visualisations for Exploring Political Concepts
Paul Nulty
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There’s no ‘Count or Predict’ but task-based selection for distributional models
Martin Riedl
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Chris Biemann
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LexSubNC: A Dataset of Lexical Substitution for Nominal Compounds
Rodrigo Wilkens
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Leonardo Zilio
|
Silvio Ricardo Cordeiro
|
Felipe Paula
|
Carlos Ramisch
|
Marco Idiart
|
Aline Villavicencio
|
Using Language Learner Data for Metaphor Detection
Egon Stemle
|
Alexander Onysko
|
Efficient Graph-based Word Sense Induction by Distributional Inclusion Vector Embeddings
Haw-Shiuan Chang
|
Amol Agrawal
|
Ananya Ganesh
|
Anirudha Desai
|
Vinayak Mathur
|
Alfred Hough
|
Andrew McCallum
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On Learning Better Embeddings from Chinese Clinical Records: Study on Combining In-Domain and Out-Domain Data
Yaqiang Wang
|
Yunhui Chen
|
Hongping Shu
|
Yongguang Jiang
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Automated Acquisition of Patterns for Coding Political Event Data: Two Case Studies
Peter Makarov
|
On the Role of Text Preprocessing in Neural Network Architectures: An Evaluation Study on Text Categorization and Sentiment Analysis
Jose Camacho-Collados
|
Mohammad Taher Pilehvar
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Using Sentiment Induction to Understand Variation in Gendered Online Communities
Lucy Li
|
Julia Mendelsohn
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Reducing Lexical Features in Parsing by Word Embeddings
Hiroya Komatsu
|
Ran Tian
|
Naoaki Okazaki
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Kentaro Inui
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Testing APSyn against Vector Cosine on Similarity Estimation
Enrico Santus
|
Emmanuele Chersoni
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Alessandro Lenci
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Chu-Ren Huang
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Philippe Blache
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http://word2vec.googlecode.com/svn/
http://bitbucket.org/omerlevy/
Field Of Study
Linguistic Trends
Embeddings
Task
Semantic Similarity
Language
English
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