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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 501–550 of 4002 papers

TitleStatusHype
Automatic Noun Compound Interpretation using Deep Neural Networks and Word Embeddings—0
Automatic Term Extraction from Newspaper Corpora: Making the Most of Specificity and Common Features—0
Automatic Transformation of Clinical Narratives into Structured Format—0
Automatic Triage of Mental Health Forum Posts—0
Automatic Word Association Norms (AWAN)—0
Automating Idea Unit Segmentation and Alignment for Assessing Reading Comprehension via Summary Protocol Analysis—0
A Dynamic Window Neural Network for CCG Supertagging—0
A Comparison of Domain-based Word Polarity Estimation using different Word Embeddings—0
AWE: Asymmetric Word Embedding for Textual Entailment—0
An Empirical Study of Discriminative Sequence Labeling Models for Vietnamese Text Processing—0
A Challenge Set and Methods for Noun-Verb Ambiguity—0
A data-driven strategy to combine word embeddings in information retrieval—0
Bootstrapping NLU Models with Multi-task Learning—0
Borrow a Little from your Rich Cousin: Using Embeddings and Polarities of English Words for Multilingual Sentiment Classification—0
ARHNet - Leveraging Community Interaction for Detection of Religious Hate Speech in Arabic—0
Argument from Old Man’s View: Assessing Social Bias in Argumentation—0
A Margin-based Loss with Synthetic Negative Samples for Continuous-output Machine Translation—0
A Machine Learning Application for Raising WASH Awareness in the Times of COVID-19 Pandemic—0
Argumentative Topology: Finding Loop(holes) in Logic—0
Adaptive Compression of Word Embeddings—0
Bootstrapping Multilingual AMR with Contextual Word Alignments—0
bot.zen @ EmpiriST 2015 - A minimally-deep learning PoS-tagger (trained for German CMC and Web data)—0
Breaking Down Word Semantics from Pre-trained Language Models through Layer-wise Dimension Selection—0
ArGoT: A Glossary of Terms extracted from the arXiv—0
Alzheimer Disease Classification through ASR-based Transcriptions: Exploring the Impact of Punctuation and Pauses—0
A* CCG Parsing with a Supertag-factored Model—0
“Are you calling for the vaporizer you ordered?” Combining Search and Prediction to Identify Orders in Contact Centers—0
Are Word Embeddings Really a Bad Fit for the Estimation of Thematic Fit?—0
Accurate Dependency Parsing and Tagging of Latin—0
BLISS in Non-Isometric Embedding Spaces—0
Are Word Embedding-based Features Useful for Sarcasm Detection?—0
A LSTM Approach with Sub-Word Embeddings for Mongolian Phrase Break Prediction—0
Adapting word2vec to Named Entity Recognition—0
A Review on Deep Learning Techniques Applied to Answer Selection—0
A Review of Standard Text Classification Practices for Multi-label Toxicity Identification of Online Content—0
A Locally Linear Procedure for Word Translation—0
Blinov: Distributed Representations of Words for Aspect-Based Sentiment Analysis at SemEval 2014—0
Boosting Named Entity Recognition with Neural Character Embeddings—0
All-words Word Sense Disambiguation Using Concept Embeddings—0
A Review of Cross-Domain Text-to-SQL Models—0
Bit Cipher -- A Simple yet Powerful Word Representation System that Integrates Efficiently with Language Models—0
A Retrofitting Model for Incorporating Semantic Relations into Word Embeddings—0
Adapting Topic Models using Lexical Associations with Tree Priors—0
BLCU\_NLP at SemEval-2018 Task 12: An Ensemble Model for Argument Reasoning Based on Hierarchical Attention—0
Adapting Pre-trained Word Embeddings For Use In Medical Coding—0
Are Girls Neko or Sh\=ojo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization—0
All That Glitters is Not Gold: A Gold Standard of Adjective-Noun Collocations for German—0
BIT at SemEval-2016 Task 1: Sentence Similarity Based on Alignments and Vector with the Weight of Information Content—0
Blind signal decomposition of various word embeddings based on join and individual variance explained—0
Bootstrap Domain-Specific Sentiment Classifiers from Unlabeled Corpora—0
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