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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 751–775 of 4002 papers

TitleStatusHype
CogALex-V Shared Task: CGSRC - Classifying Semantic Relations using Convolutional Neural Networks—0
CogALex-V Shared Task: GHHH - Detecting Semantic Relations via Word Embeddings—0
CogALex-V Shared Task: LOPE—0
Artificial intelligence prediction of stock prices using social media—0
CogniFNN: A Fuzzy Neural Network Framework for Cognitive Word Embedding Evaluation—0
Artificial mental phenomena: Psychophysics as a framework to detect perception biases in AI models—0
CogniVal in Action: An Interface for Customizable Cognitive Word Embedding Evaluation—0
CogNLP-Sheffield at CMCL 2021 Shared Task: Blending Cognitively Inspired Features with Transformer-based Language Models for Predicting Eye Tracking Patterns—0
Coherence models in schizophrenia—0
COIN – an Inexpensive and Strong Baseline for Predicting Out of Vocabulary Word Embeddings—0
Co-learning of Word Representations and Morpheme Representations—0
A semi-supervised model for Persian rumor verification based on content information—0
A Semi-universal Pipelined Approach to the CoNLL 2017 UD Shared Task—0
A Model of Zero-Shot Learning of Spoken Language Understanding—0
Combination of Domain Knowledge and Deep Learning for Sentiment Analysis of Short and Informal Messages on Social Media—0
Combining Acoustics, Content and Interaction Features to Find Hot Spots in Meetings—0
BLCU\_NLP at SemEval-2018 Task 12: An Ensemble Model for Argument Reasoning Based on Hierarchical Attention—0
Combining Character and Word Embeddings for the Detection of Offensive Language in Arabic—0
Combining Contrastive Learning and Knowledge Graph Embeddings to develop medical word embeddings for the Italian language—0
Combining Discourse Markers and Cross-lingual Embeddings for Synonym--Antonym Classification—0
Addressing Low-Resource Scenarios with Character-aware Embeddings—0
Combining Long Short Term Memory and Convolutional Neural Network for Cross-Sentence n-ary Relation Extraction—0
Combining neural and knowledge-based approaches to Named Entity Recognition in Polish—0
Combining Pretrained High-Resource Embeddings and Subword Representations for Low-Resource Languages—0
Antonymy-Synonymy Discrimination through the Repelling Parasiamese Neural Network—0
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