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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 676–700 of 4002 papers

TitleStatusHype
Inferring Prototypes for Multi-Label Few-Shot Image Classification with Word Vector Guided Attention—0
Sdutta at ComMA@ICON: A CNN-LSTM Model for Hate Detection—0
Resolving Prepositional Phrase Attachment Ambiguities with Contextualized Word EmbeddingsCode0
Retrofitting of Pre-trained Emotion Words with VAD-dimensions and the Plutchik Emotions—0
An Exploratory Study on Temporally Evolving Discussion around Covid-19 using Diachronic Word Embeddings—0
Using Word Embeddings to Quantify Ethnic Stereotypes in 12 years of Spanish News—0
Abstractive Text Summarization: Enhancing Sequence-to-Sequence Models Using Word Sense Disambiguation and Semantic Content Generalization—0
A Comparative Study of Transformers on Word Sense Disambiguation—0
Chemical Identification and Indexing in PubMed Articles via BERT and Text-to-Text Approaches—0
Bilingual Topic Models for Comparable Corpora—0
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster AssignmentCode0
Keyword Assisted Embedded Topic ModelCode1
More Romanian word embeddings from the RETEROM project—0
Isomorphic Cross-lingual Embeddings for Low-Resource Languages—0
Metaphor Detection for Low Resource Languages: From Zero-Shot to Few-Shot Learning in Middle High German—0
Discrete Wavelet Transform for Efficient Word Embeddings and Sentence Encoding—0
Unsupervised Domain Adaptation with Contrastive Learning for Cross-domain Chinese NER—0
Cross-lingual Word Embeddings in Hyperbolic Space—0
Improving Word Translation via Two-Stage Contrastive LearningCode1
Crossword: Estimating Unknown Embeddings using Cross Attention and Alignment Strategies—0
Softmax Bottleneck Makes Language Models Unable to Represent Multi-mode Word Distributions—0
Sentence Selection Strategies for Distilling Word Embeddings from BERT—0
Non-Linear Relational Information Probing in Word Embeddings—0
FeelsGoodMan: Inferring Semantics of Twitch Neologisms—0
Looking Into the Black Box - How Are Idioms Processed in BERT?—0
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