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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 651–700 of 4002 papers

TitleStatusHype
Addressing the Challenges of Cross-Lingual Hate Speech Detection—0
Compressing Word Embeddings Using Syllables—0
Diagnosing BERT with Retrieval HeuristicsCode0
D-Graph: AI-Assisted Design Concept Exploration Graph—0
Embeddings Evaluation Using a Novel Measure of Semantic SimilarityCode0
HuSpaCy: an industrial-strength Hungarian natural language processing toolkitCode1
Applying Word Embeddings to Measure Valence in Information Operations Targeting Journalists in Brazil—0
Semi-automatic WordNet Linking using Word Embeddings—0
Predicting Influenza A Viral Host Using PSSM and Word Embeddings—0
Which Student is Best? A Comprehensive Knowledge Distillation Exam for Task-Specific BERT Models—0
Simple, Interpretable and Stable Method for Detecting Words with Usage Change across CorporaCode1
"A Passage to India": Pre-trained Word Embeddings for Indian Languages—0
Traffic event description based on Twitter data using Unsupervised Learning Methods for Indian road conditions—0
Zero-shot and Few-shot Learning with Knowledge Graphs: A Comprehensive Survey—0
Joint Mitigation of Interactional Bias—0
Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource LanguagesCode0
Unsupervised Matching of Data and TextCode0
Identification of Biased Terms in News Articles by Comparison of Outlet-specific Word Embeddings—0
WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language modelsCode1
Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic Information PreservingCode0
Few-Shot NLU with Vector Projection Distance and Abstract Triangular CRF—0
Combining Textual Features for the Detection of Hateful and Offensive LanguageCode0
Emotion-Cause Pair Extraction in Customer Reviews—0
BERTMap: A BERT-based Ontology Alignment System—0
Open-CyKG: An Open Cyber Threat Intelligence Knowledge GraphCode1
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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