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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 2101–2150 of 4002 papers

TitleStatusHype
Reverse Transfer Learning: Can Word Embeddings Trained for Different NLP Tasks Improve Neural Language Models?—0
Revisiting Additive Compositionality: AND, OR and NOT Operations with Word Embeddings—0
Revisiting Additive Compositionality: AND, OR, and NOT Operations with Word Embeddings—0
Revisiting Embedding Features for Simple Semi-supervised Learning—0
Revisiting Representation Degeneration Problem in Language Modeling—0
Revisiting Statistical Laws of Semantic Shift in Romance Cognates—0
Revisiting Supertagging and Parsing: How to Use Supertags in Transition-Based Parsing—0
Revisiting the Context Window for Cross-lingual Word Embeddings—0
Revisiting Word Embeddings in the LLM Era—0
ReWE: Regressing Word Embeddings for Regularization of Neural Machine Translation Systems—0
Right-truncatable Neural Word Embeddings—0
Risk Bounds for Transferring Representations With and Without Fine-Tuning—0
Robust and Consistent Estimation of Word Embedding for Bangla Language by fine-tuning Word2Vec Model—0
Robust Backed-off Estimation of Out-of-Vocabulary Embeddings—0
Robust Concept Erasure Using Task Vectors—0
Robust Word Vectors: Context-Informed Embeddings for Noisy Texts—0
Roleo: Visualising Thematic Fit Spaces on the Web—0
Romanian micro-blogging named entity recognition including health-related entities—0
Room to Glo: A Systematic Comparison of Semantic Change Detection Approaches with Word Embeddings—0
Rotate King to get Queen: Word Relationships as Orthogonal Transformations in Embedding Space—0
Rotations and Interpretability of Word Embeddings: the Case of the Russian Language—0
RPD: A Distance Function Between Word Embeddings—0
R-SFLLM: Jamming Resilient Framework for Split Federated Learning with Large Language Models—0
RS\_GV at SemEval-2021 Task 1: Sense Relative Lexical Complexity Prediction—0
RUFINO at SemEval-2017 Task 2: Cross-lingual lexical similarity by extending PMI and word embeddings systems with a Swadesh's-like list—0
Ruminating Word Representations with Random Noised Masker—0
Ruminating Word Representations with Random Noise Masking—0
Rumor Detection by Multi-task Suffix Learning based on Time-series Dual Sentiments—0
RuSentiment: An Enriched Sentiment Analysis Dataset for Social Media in Russian—0
Sampled Image Tagging and Retrieval Methods on User Generated Content—0
SAPPHIRE: Simple Aligner for Phrasal Paraphrase with Hierarchical Representation—0
Sarcastic or Not: Word Embeddings to Predict the Literal or Sarcastic Meaning of Words—0
SAT Based Analogy Evaluation Framework for Persian Word Embeddings—0
SB@GU at the Complex Word Identification 2018 Shared Task—0
Scene Classification in Indoor Environments for Robots using Context Based Word Embeddings—0
Scientific document summarization via citation contextualization and scientific discourse—0
Sdutta at ComMA@ICON: A CNN-LSTM Model for Hate Detection—0
SEAGLE: A Platform for Comparative Evaluation of Semantic Encoders for Information Retrieval—0
Searching for the X-Factor: Exploring Corpus Subjectivity for Word Embeddings—0
Sectioning of Biomedical Abstracts: A Sequence of Sequence Classification Task—0
Seeing is Knowing! Fact-based Visual Question Answering using Knowledge Graph Embeddings—0
Seeing the advantage: visually grounding word embeddings to better capture human semantic knowledge—0
SEE: Sememe Entanglement Encoding for Transformer-bases Models Compression—0
Selection Strategies for Commonsense Knowledge—0
Selective Co-occurrences for Word-Emotion Association—0
Self-Attention Architectures for Answer-Agnostic Neural Question Generation—0
Self-Attention for Incomplete Utterance Rewriting—0
Self-Reflective Sentiment Analysis—0
Self-Supervised Acoustic Word Embedding Learning via Correspondence Transformer Encoder—0
Self-Supervised Detection of Contextual Synonyms in a Multi-Class Setting: Phenotype Annotation Use Case—0
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