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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 2801–2850 of 4002 papers

TitleStatusHype
WordRep: A Benchmark for Research on Learning Word Representations—0
Words are Vectors, Dependencies are Matrices: Learning Word Embeddings from Dependency Graphs—0
Word Semantic Representations using Bayesian Probabilistic Tensor Factorization—0
Word Sense Disambiguation for 158 Languages using Word Embeddings Only—0
Word Sense Distance in Human Similarity Judgements and Contextualised Word Embeddings—0
Word Sense Filtering Improves Embedding-Based Lexical Substitution—0
Word Sense Induction using Knowledge Embeddings—0
Word sense induction using word embeddings and community detection in complex networks—0
Word Sense Induction with Knowledge Distillation from BERT—0
Word-specific tonal realizations in Mandarin—0
Wordsurf : un outil pour naviguer dans un espace de « Word Embeddings » (Wordsurf : a tool to surf in a ``word embeddings'' space)—0
Word vectors, reuse, and replicability: Towards a community repository of large-text resources—0
WOVe: Incorporating Word Order in GloVe Word Embeddings—0
XLNET-GRU Sentiment Regression Model for Cryptocurrency News in English and Malay—0
XMU Neural Machine Translation Systems for WAT 2017—0
Contextualized End-to-End Neural Entity Linking—0
YNUDLG at SemEval-2017 Task 4: A GRU-SVM Model for Sentiment Classification and Quantification in Twitter—0
YNU-HPCC at IJCNLP-2017 Task 5: Multi-choice Question Answering in Exams Using an Attention-based LSTM Model—0
You shall know a piece by the company it keeps. Chess plays as a data for word2vec models—0
Yseop at FinSim-3 Shared Task 2021: Specializing Financial Domain Learning with Phrase Representations—0
YZU-NLP at EmoInt-2017: Determining Emotion Intensity Using a Bi-directional LSTM-CNN Model—0
YZU-NLP Team at SemEval-2016 Task 4: Ordinal Sentiment Classification Using a Recurrent Convolutional Network—0
Zara Returns: Improved Personality Induction and Adaptation by an Empathetic Virtual Agent—0
Zero-Inflated Exponential Family Embeddings—0
Zero-Shot Activity Recognition with Videos—0
Zero-Shot Cross-Lingual Opinion Target Extraction—0
Zero-Shot Cross-Lingual Transfer is a Hard Baseline to Beat in German Fine-Grained Entity Typing—0
Zero-Shot Visual Question Answering—0
Text Classification Components for Detecting Descriptions and Names of CAD models—0
Zur Darstellung eines mehrstufigen Prototypbegriffs in der multilingualen automatischen Sprachgenerierung: vom Korpus über word embeddings bis hin zum automatischen Wörterbuch—0
Text2Node: a Cross-Domain System for Mapping Arbitrary Phrases to a Taxonomy—0
Self-supervised audio representation learning for mobile devices—0
Emotional Embeddings: Refining Word Embeddings to Capture Emotional Content of Words—0
Examining Structure of Word Embeddings with PCA—0
Regularization Advantages of Multilingual Neural Language Models for Low Resource Domains—0
On the Robustness of Unsupervised and Semi-supervised Cross-lingual Word Embedding Learning—0
Disentangling Latent Emotions of Word Embeddings on Complex Emotional Narratives—0
Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings—0
Low-Rank Approximation of Matrices for PMI-based Word Embeddings—0
1Cademy at Semeval-2022 Task 1: Investigating the Effectiveness of Multilingual, Multitask, and Language-Agnostic Tricks for the Reverse Dictionary Task—0
Misinforming LLMs: vulnerabilities, challenges and opportunities—0
Decoupled Vocabulary Learning Enables Zero-Shot Translation from Unseen Languages—0
A Simplified Retriever to Improve Accuracy of Phenotype Normalizations by Large Language Models—0
300-sparsans at SemEval-2018 Task 9: Hypernymy as interaction of sparse attributes—0
4chan & 8chan embeddings—0
A bag-of-concepts model improves relation extraction in a narrow knowledge domain with limited data—0
A Bayesian approach to uncertainty in word embedding bias estimation—0
ABDN at SemEval-2018 Task 10: Recognising Discriminative Attributes using Context Embeddings and WordNet—0
Abelian Neural Networks—0
A bilingual approach to specialised adjectives through word embeddings in the karstology domain—0
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