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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 2101–2150 of 4002 papers

TitleStatusHype
Identification, Interpretability, and Bayesian Word EmbeddingsCode0
SWOW-8500: Word Association task for Intrinsic Evaluation of Word Embeddings—0
Clustering-Based Article Identification in Historical NewspapersCode0
Stance Classification, Outcome Prediction, and Impact Assessment: NLP Tasks for Studying Group Decision-Making—0
Multilingual segmentation based on neural networks and pre-trained word embeddings—0
Suicide Risk Assessment on Social Media: USI-UPF at the CLPsych 2019 Shared Task—0
Deep Learning Techniques for Humor Detection in Hindi-English Code-Mixed Tweets—0
Learning Unsupervised Multilingual Word Embeddings with Incremental Multilingual Hubs—0
THU\_NGN at SemEval-2019 Task 3: Dialog Emotion Classification using Attentional LSTM-CNN—0
A k-Nearest Neighbor Approach towards Multi-level Sequence Labeling—0
Modeling Personal Biases in Language Use by Inducing Personalized Word Embeddings—0
Incorporating Emoji Descriptions Improves Tweet Classification—0
Text Similarity Estimation Based on Word Embeddings and Matrix Norms for Targeted Marketing—0
Know-Center at SemEval-2019 Task 5: Multilingual Hate Speech Detection on Twitter using CNNs—0
EmoDet at SemEval-2019 Task 3: Emotion Detection in Text using Deep Learning—0
EMOMINER at SemEval-2019 Task 3: A Stacked BiLSTM Architecture for Contextual Emotion Detection in Text—0
Learning Bilingual Sentiment-Specific Word Embeddings without Cross-lingual Supervision—0
EmoSense at SemEval-2019 Task 3: Bidirectional LSTM Network for Contextual Emotion Detection in Textual ConversationsCode0
JU\_ETCE\_17\_21 at SemEval-2019 Task 6: Efficient Machine Learning and Neural Network Approaches for Identifying and Categorizing Offensive Language in TweetsCode0
CLaC Lab at SemEval-2019 Task 3: Contextual Emotion Detection Using a Combination of Neural Networks and SVM—0
Word Embeddings (Also) Encode Human Personality StereotypesCode0
Word Embedding-Based Automatic MT Evaluation Metric using Word Position Information—0
LaSTUS/TALN at SemEval-2019 Task 6: Identification and Categorization of Offensive Language in Social Media with Attention-based Bi-LSTM model—0
Team Bertha von Suttner at SemEval-2019 Task 4: Hyperpartisan News Detection using ELMo Sentence Representation Convolutional Network—0
INF-HatEval at SemEval-2019 Task 5: Convolutional Neural Networks for Hate Speech Detection Against Women and Immigrants on Twitter—0
Transfer Learning in Natural Language Processing—0
Opinion Mining with Deep Contextualized Embeddings—0
GWU NLP Lab at SemEval-2019 Task 3 : EmoContext: Effectiveness ofContextual Information in Models for Emotion Detection inSentence-level at Multi-genre Corpus—0
Measuring and Modeling Language Change—0
GSI-UPM at SemEval-2019 Task 5: Semantic Similarity and Word Embeddings for Multilingual Detection of Hate Speech Against Immigrants and Women on Twitter—0
DS at SemEval-2019 Task 9: From Suggestion Mining with neural networks to adversarial cross-domain classification—0
SWAP at SemEval-2019 Task 3: Emotion detection in conversations through Tweets, CNN and LSTM deep neural networksCode0
GL at SemEval-2019 Task 5: Identifying hateful tweets with a deep learning approach.—0
Pre-trained Contextualized Character Embeddings Lead to Major Improvements in Time Normalization: a Detailed Analysis—0
SINAI-DL at SemEval-2019 Task 5: Recurrent networks and data augmentation by paraphrasing—0
Combining Discourse Markers and Cross-lingual Embeddings for Synonym--Antonym Classification—0
UPV-28-UNITO at SemEval-2019 Task 7: Exploiting Post's Nesting and Syntax Information for Rumor Stance Classification—0
USF at SemEval-2019 Task 6: Offensive Language Detection Using LSTM With Word Embeddings—0
Subword-based Compact Reconstruction of Word EmbeddingsCode0
STUFIIT at SemEval-2019 Task 5: Multilingual Hate Speech Detection on Twitter with MUSE and ELMo Embeddings—0
T\"upa at SemEval-2019 Task1: (Almost) feature-free Semantic Parsing—0
Atalaya at SemEval 2019 Task 5: Robust Embeddings for Tweet Classification—0
Beyond Context: A New Perspective for Word Embeddings—0
Figure Eight at SemEval-2019 Task 3: Ensemble of Transfer Learning Methods for Contextual Emotion Detection—0
Learning to Respond to Mixed-code Queries using Bilingual Word Embeddings—0
Stop PropagHate at SemEval-2019 Tasks 5 and 6: Are abusive language classification results reproducible?Code0
THU\_NGN at SemEval-2019 Task 12: Toponym Detection and Disambiguation on Scientific Papers—0
sthruggle at SemEval-2019 Task 5: An Ensemble Approach to Hate Speech Detection—0
Leveraging Pretrained Word Embeddings for Part-of-Speech Tagging of Code Switching Data—0
The Pupil Has Become the Master: Teacher-Student Model-Based Word Embedding Distillation with Ensemble LearningCode0
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