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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 1751–1800 of 4002 papers

TitleStatusHype
Improving Interpretability of Word Embeddings by Generating Definition and Usage—0
CoSimLex: A Resource for Evaluating Graded Word Similarity in ContextCode0
Machine Translation with Cross-lingual Word EmbeddingsCode0
Multilingual aspect clustering for sentiment analysisCode0
Can AI Generate Love Advice?: Toward Neural Answer Generation for Non-Factoid Questions—0
Massive vs. Curated Word Embeddings for Low-Resourced Languages. The Case of Yorùbá and TwiCode0
Measuring Social Bias in Knowledge Graph Embeddings—0
Natural Alpha Embeddings—0
A Robust Self-Learning Method for Fully Unsupervised Cross-Lingual Mappings of Word Embeddings: Making the Method Robustly Reproducible as WellCode0
EduBERT: Pretrained Deep Language Models for Learning Analytics—0
Incorporating Sub-Word Level Information in Language Invariant Neural Event Detection—0
Deconstructing and reconstructing word embedding algorithms—0
Inducing Relational Knowledge from BERT—0
RETRO: Relation Retrofitting For In-Database Machine Learning on Textual Data—0
Word Embedding based New Corpus for Low-resourced Language: Sindhi—0
Taking a Stance on Fake News: Towards Automatic Disinformation Assessment via Deep Bidirectional Transformer Language Models for Stance Detection—0
Hybrid Text Feature Modeling for Disease Group Prediction using Unstructured Physician Notes—0
City2City: Translating Place Representations across Cities—0
Word-Class Embeddings for Multiclass Text ClassificationCode0
Visual Summarization of Scholarly Videos using Word Embeddings and Keyphrase Extraction—0
A Causal Inference Method for Reducing Gender Bias in Word Embedding RelationsCode0
Towards robust word embeddings for noisy textsCode0
Causally Denoise Word Embeddings Using Half-Sibling RegressionCode0
Enhancing Out-Of-Domain Utterance Detection with Data Augmentation Based on Word Embeddings—0
Anaphora Resolution in Dialogue Systems for South Asian Languages—0
Multilingual Culture-Independent Word Analogy Datasets—0
Topical Phrase Extraction from Clinical Reports by Incorporating both Local and Global Context—0
Empirical Autopsy of Deep Video Captioning Frameworks—0
SemanticZ at SemEval-2016 Task 3: Ranking Relevant Answers in Community Question Answering Using Semantic Similarity Based on Fine-tuned Word EmbeddingsCode0
Error Analysis for Vietnamese Named Entity Recognition on Deep Neural Network Models—0
Bootstrapping NLU Models with Multi-task Learning—0
Learning Relationships between Text, Audio, and Video via Deep Canonical Correlation for Multimodal Language Analysis—0
What do you mean, BERT? Assessing BERT as a Distributional Semantics Model—0
word2ket: Space-efficient Word Embeddings inspired by Quantum EntanglementCode0
Learning Multi-Sense Word Distributions using Approximate Kullback-Leibler Divergence—0
How to Evaluate Word Representations of Informal Domain?Code0
Contextualized End-to-End Neural Entity Linking—0
Towards Understanding Gender Bias in Relation ExtractionCode0
Ruminating Word Representations with Random Noised Masker—0
Neural Graph Embedding Methods for Natural Language ProcessingCode0
Interactive Refinement of Cross-Lingual Word EmbeddingsCode0
Should All Cross-Lingual Embeddings Speak English?Code0
How Can BERT Help Lexical Semantics Tasks?—0
Invariance and identifiability issues for word embeddings—0
A Deep Learning approach for Hindi Named Entity Recognition—0
Incremental Sense Weight Training for the Interpretation of Contextualized Word Embeddings—0
Integrating Dictionary Feature into A Deep Learning Model for Disease Named Entity Recognition—0
Assessing Social and Intersectional Biases in Contextualized Word RepresentationsCode0
Emerging Cross-lingual Structure in Pretrained Language Models—0
Deep Contextualized Word Embeddings in Transition-Based and Graph-Based Dependency Parsing - A Tale of Two Parsers Revisited—0
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