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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 3501–3550 of 4002 papers

TitleStatusHype
Empowering Segmentation Ability to Multi-modal Large Language ModelsCode0
Empower Sequence Labeling with Task-Aware Neural Language ModelCode0
Learning of Colors from Color Names: Distribution and Point EstimationCode0
Unsupervised Text Segmentation Using Semantic Relatedness GraphsCode0
Online Learning of Interpretable Word EmbeddingsCode0
Learning Dynamic Contextualised Word Embeddings via Template-based Temporal AdaptationCode0
Word class flexibility: A deep contextualized approachCode0
Encoding Category Trees Into Word-Embeddings Using Geometric ApproachCode0
On Measuring and Mitigating Biased Inferences of Word EmbeddingsCode0
Learning Efficient Task-Specific Meta-Embeddings with Word PrismsCode0
Encoding word order in complex embeddingsCode0
Learning Eligibility in Cancer Clinical Trials using Deep Neural NetworksCode0
End-to-End Neural Ad-hoc Ranking with Kernel PoolingCode0
End-to-end Recurrent Neural Network Models for Vietnamese Named Entity Recognition: Word-level vs. Character-levelCode0
End-to-End Text Classification via Image-based Embedding using Character-level NetworksCode0
On Measuring Social Biases in Sentence EncodersCode0
Variational Sequential Labelers for Semi-Supervised LearningCode0
Semantics-aware BERT for Language UnderstandingCode0
Alternative Weighting Schemes for ELMo EmbeddingsCode0
Semantic Sensitive TF-IDF to Determine Word Relevance in DocumentsCode0
Enhanced word embeddings using multi-semantic representation through lexical chainsCode0
ML-EAT: A Multilevel Embedding Association Test for Interpretable and Transparent Social ScienceCode0
Learning Gender-Neutral Word EmbeddingsCode0
Enhancing biomedical word embeddings by retrofitting to verb clustersCode0
Semantics or spelling? Probing contextual word embeddings with orthographic noiseCode0
On the Dimensionality of Word EmbeddingCode0
Enhancing Deep Learning with Embedded Features for Arabic Named Entity RecognitionCode0
On the Downstream Performance of Compressed Word EmbeddingsCode0
Classifying Relations by Ranking with Convolutional Neural NetworksCode0
Learning language through picturesCode0
Learning language variations in news corpora through differential embeddingsCode0
Learning Lexical Subspaces in a Distributional Vector SpaceCode0
Learning Meta-Embeddings by Using Ensembles of Embedding SetsCode0
Semantic Structure and Interpretability of Word EmbeddingsCode0
On the Effect of Low-Frequency Terms on Neural-IR ModelsCode0
SemSup: Semantic Supervision for Simple and Scalable Zero-shot GeneralizationCode0
VAST: The Valence-Assessing Semantics Test for Contextualizing Language ModelsCode0
Learning Multilingual Word Embeddings in Latent Metric Space: A Geometric ApproachCode0
Enhancing Word Embeddings with Knowledge Extracted from Lexical ResourcesCode0
Transformers without Tears: Improving the Normalization of Self-AttentionCode0
SemanticZ at SemEval-2016 Task 3: Ranking Relevant Answers in Community Question Answering Using Semantic Similarity Based on Fine-tuned Word EmbeddingsCode0
A Survey on Sentence Embedding Models Performance for Patent AnalysisCode0
Temporal Word Analogies: Identifying Lexical Replacement with Diachronic Word EmbeddingsCode0
Enriching Word Embeddings with Temporal and Spatial InformationCode0
Enriching Word Vectors with Subword InformationCode0
An Open-World Extension to Knowledge Graph Completion ModelsCode0
VCDM: Leveraging Variational Bi-encoding and Deep Contextualized Word Representations for Improved Definition ModelingCode0
Learning Neural Word Salience ScoresCode0
On the Interpretability and Significance of Bias Metrics in Texts: a PMI-based ApproachCode0
Better Summarization Evaluation with Word Embeddings for ROUGECode0
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