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Word Embeddings

Word embedding is the collective name for a set of language modeling and feature learning techniques in natural language processing (NLP) where words or phrases from the vocabulary are mapped to vectors of real numbers.

Techniques for learning word embeddings can include Word2Vec, GloVe, and other neural network-based approaches that train on an NLP task such as language modeling or document classification.

( Image credit: Dynamic Word Embedding for Evolving Semantic Discovery )

Papers

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Showing 1251–1300 of 4002 papers

TitleStatusHype
Learning Negation Scope from Syntactic Structure—0
Go Simple and Pre-Train on Domain-Specific Corpora: On the Role of Training Data for Text Classification—0
Neural Abstractive Multi-Document Summarization: Hierarchical or Flat Structure?—0
Lexical Relation Mining in Neural Word Embeddings—0
Cross-lingual Annotation Projection in Legal TextsCode0
Augmenting NLP models using Latent Feature Interpolations—0
Leveraging Contextual Embeddings and Idiom Principle for Detecting Idiomaticity in Potentially Idiomatic Expressions—0
Towards Augmenting Lexical Resources for Slang and African American English—0
TUE at SemEval-2020 Task 1: Detecting Semantic Change by Clustering Contextual Word Embeddings—0
Coordination Boundary Identification without Labeled Data for Compound Terms Disambiguation—0
Manifold Learning-based Word Representation Refinement Incorporating Global and Local Information—0
UNT Linguistics at SemEval-2020 Task 12: Linear SVC with Pre-trained Word Embeddings as Document Vectors and Targeted Linguistic Features—0
Contextualized Embeddings for Enriching Linguistic Analyses on Politeness—0
Consistent Structural Relation Learning for Zero-Shot Segmentation—0
Improving Word Embeddings through Iterative Refinement of Word- and Character-level Models—0
A Co-Attentive Cross-Lingual Neural Model for Dialogue Breakdown DetectionCode0
Intrinsic analysis for dual word embedding space models—0
Assessing Polyseme Sense Similarity through Co-predication Acceptability and Contextualised Embedding Distance—0
Comparison between Voting Classifier and Deep Learning methods for Arabic Dialect Identification—0
TemporalTeller at SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection with Temporal Referencing—0
Amplifying the Range of News Stories with Creativity: Methods and their Evaluation, in Portuguese—0
Combining Word Embeddings with Bilingual Orthography Embeddings for Bilingual Dictionary Induction—0
SU-NLP at SemEval-2020 Task 12: Offensive Language IdentifiCation in Turkish Tweets—0
A Simple and Effective Usage of Word Clusters for CBOW ModelCode0
Combining financial word embeddings and knowledge-based features for financial text summarization UC3M-MC System at FNS-2020Code0
CogniVal in Action: An Interface for Customizable Cognitive Word Embedding Evaluation—0
CMCE at SemEval-2020 Task 1: Clustering on Manifolds of Contextualized Embeddings to Detect Historical Meaning ShiftsCode0
Argument from Old Man’s View: Assessing Social Bias in Argumentation—0
A Locally Linear Procedure for Word Translation—0
Tiny Word Embeddings Using Globally Informed Reconstruction—0
A Review of Cross-Domain Text-to-SQL Models—0
A Retrofitting Model for Incorporating Semantic Relations into Word Embeddings—0
CLaC at SMM4H 2020: Birth Defect Mention Detection—0
CLaC at SemEval-2020 Task 5: Muli-task Stacked Bi-LSTMs—0
CitiusNLP at SemEval-2020 Task 3: Comparing Two Approaches for Word Vector Contextualization—0
Joint Training for Learning Cross-lingual Embeddings with Sub-word Information without Parallel Corpora—0
SMM4H Shared Task 2020 - A Hybrid Pipeline for Identifying Prescription Drug Abuse from Twitter: Machine Learning, Deep Learning, and Post-Processing—0
Can Existing Methods Debias Languages Other than English? First Attempt to Analyze and Mitigate Japanese Word Embeddings—0
Multimodal Review Generation with Privacy and Fairness AwarenessCode0
Embeddings in Natural Language Processing—0
UZH at SemEval-2020 Task 3: Combining BERT with WordNet Sense Embeddings to Predict Graded Word Similarity Changes—0
A Language-Based Approach to Fake News Detection Through Interpretable Features and BRNN—0
UAlberta at SemEval-2020 Task 2: Using Translations to Predict Cross-Lingual Entailment—0
SHIKEBLCU at SemEval-2020 Task 2: An External Knowledge-enhanced Matrix for Multilingual and Cross-Lingual Lexical Entailment—0
Do Word Embeddings Capture Spelling Variation?Code0
DoTheMath at SemEval-2020 Task 12 : Deep Neural Networks with Self Attention for Arabic Offensive Language Detection—0
Meta-Embeddings for Natural Language Inference and Semantic Similarity tasks—0
Interdependencies of Gender and Race in Contextualized Word Embeddings—0
“Shakespeare in the Vectorian Age” – An evaluation of different word embeddings and NLP parameters for the detection of Shakespeare quotes—0
Expert Concept-Modeling Ground Truth Construction for Word Embeddings Evaluation in Concept-Focused DomainsCode0
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