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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 1051–1100 of 4002 papers

TitleStatusHype
Domain-Specific Word Embeddings with Structure PredictionCode0
Deep Unordered Composition Rivals Syntactic Methods for Text ClassificationCode0
Deep word embeddings for visual speech recognitionCode0
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling MechanismsCode0
Don't Settle for Average, Go for the Max: Fuzzy Sets and Max-Pooled Word VectorsCode0
Do Word Embeddings Capture Spelling Variation?Code0
Definition Frames: Using Definitions for Hybrid Concept RepresentationsCode0
Definition Modeling: Learning to define word embeddings in natural languageCode0
Document Embedding with Paragraph VectorsCode0
Do CoNLL-2003 Named Entity Taggers Still Work Well in 2023?Code0
Degree-Aware Alignment for Entities in TailCode0
BB_twtr at SemEval-2017 Task 4: Twitter Sentiment Analysis with CNNs and LSTMsCode0
An Interpretable and Uncertainty Aware Multi-Task Framework for Multi-Aspect Sentiment AnalysisCode0
A Neural Language Model for Dynamically Representing the Meanings of Unknown Words and Entities in a DiscourseCode0
Does mBERT understand Romansh? Evaluating word embeddings using word alignmentCode0
Efficient Structured Inference for Transition-Based Parsing with Neural Networks and Error StatesCode0
Distilling Word Meaning in Context from Pre-trained Language ModelsCode0
EigenSent: Spectral sentence embeddings using higher-order Dynamic Mode DecompositionCode0
Bad Company---Neighborhoods in Neural Embedding Spaces Considered HarmfulCode0
Do Acoustic Word Embeddings Capture Phonological Similarity? An Empirical StudyCode0
Domain Adapted Word Embeddings for Improved Sentiment ClassificationCode0
Eating Garlic Prevents COVID-19 Infection: Detecting Misinformation on the Arabic Content of TwitterCode0
Discovering emergent connections in quantum physics research via dynamic word embeddingsCode0
emoji2vec: Learning Emoji Representations from their DescriptionCode0
Dependency Sensitive Convolutional Neural Networks for Modeling Sentences and DocumentsCode0
Discriminating between Lexico-Semantic Relations with the Specialization Tensor ModelCode0
Empower Sequence Labeling with Task-Aware Neural Language ModelCode0
Encoding Category Trees Into Word-Embeddings Using Geometric ApproachCode0
Discovering and Interpreting Biased Concepts in Online CommunitiesCode0
Disentangling dialects: a neural approach to Indo-Aryan historical phonology and subgroupingCode0
DisCoDisCo at the DISRPT2021 Shared Task: A System for Discourse Segmentation, Classification, and Connective DetectionCode0
Deriving Word Vectors from Contextualized Language Models using Topic-Aware Mention SelectionCode0
An Evaluation Dataset for Legal Word Embedding: A Case Study On Chinese CodexCode0
Design and Implementation of a Quantum Kernel for Natural Language ProcessingCode0
Enhancing Deep Learning with Embedded Features for Arabic Named Entity RecognitionCode0
An Empirical Study on Leveraging Position Embeddings for Target-oriented Opinion Words ExtractionCode0
Discourse Relation Embeddings: Representing the Relations between Discourse Segments in Social MediaCode0
ESTeR: Combining Word Co-occurrences and Word Associations for Unsupervised Emotion DetectionCode0
Detecting Anxiety through RedditCode0
A Comprehensive Comparison of Word Embeddings in Event & Entity Coreference ResolutionCode0
CWTM: Leveraging Contextualized Word Embeddings from BERT for Neural Topic ModelingCode0
Axis Tour: Word Tour Determines the Order of Axes in ICA-transformed EmbeddingsCode0
Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual RetrievalCode0
Evaluating Neural Word Embeddings for SanskritCode0
A Bi-Encoder LSTM Model For Learning Unstructured DialogsCode0
Evaluating Unsupervised Dutch Word Embeddings as a Linguistic ResourceCode0
Evaluating Word Embeddings with Categorical ModularityCode0
Evaluation of Croatian Word EmbeddingsCode0
Evaluation of Word Vector Representations by Subspace AlignmentCode0
Deep learning for language understanding of mental health concepts derived from Cognitive Behavioural TherapyCode0
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