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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 3851–3875 of 4002 papers

TitleStatusHype
MetaLDA: a Topic Model that Efficiently Incorporates Meta informationCode0
Axis Tour: Word Tour Determines the Order of Axes in ICA-transformed EmbeddingsCode0
CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix Space ModelCode0
Word Embeddings and Convolutional Neural Network for Arabic Sentiment ClassificationCode0
Metaphor Detection for Low Resource Languages: From Zero-Shot to Few-Shot Learning in Middle High GermanCode0
Understanding Composition of Word Embeddings via Tensor DecompositionCode0
Grammatical Error Detection Using Error- and Grammaticality-Specific Word EmbeddingsCode0
Grammatical gender associations outweigh topical gender bias in crosslinguistic word embeddingsCode0
Quasi-orthonormal Encoding for Machine Learning ApplicationsCode0
Graph-based Clustering for Detecting Semantic Change Across Time and LanguagesCode0
Are you tough enough? Framework for Robustness Validation of Machine Comprehension SystemsCode0
Are We Consistently Biased? Multidimensional Analysis of Biases in Distributional Word VectorsCode0
Query and Output: Generating Words by Querying Distributed Word Representations for Paraphrase GenerationCode0
Caveats of Measuring Semantic Change of Cognates and Borrowings using Multilingual Word EmbeddingsCode0
Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional NetworksCode0
Causally Denoise Word Embeddings Using Half-Sibling RegressionCode0
Categorical Metadata Representation for Customized Text ClassificationCode0
MGAD: Multilingual Generation of Analogy DatasetsCode0
Query-by-Example Search with Discriminative Neural Acoustic Word EmbeddingsCode0
Graph-of-Tweets: A Graph Merging Approach to Sub-event IdentificationCode0
CARER: Contextualized Affect Representations for Emotion RecognitionCode0
AWE-CM Vectors: Augmenting Word Embeddings with a Clinical MetathesaurusCode0
MICE: Mining Idioms with Contextual EmbeddingsCode0
Think Globally, Embed Locally --- Locally Linear Meta-embedding of WordsCode0
Mimicking Word Embeddings using Subword RNNsCode0
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