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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 851–900 of 4002 papers

TitleStatusHype
Abstractive Text Summarization: Enhancing Sequence-to-Sequence Models Using Word Sense Disambiguation and Semantic Content Generalization—0
Resolving Prepositional Phrase Attachment Ambiguities with Contextualized Word EmbeddingsCode0
Sdutta at ComMA@ICON: A CNN-LSTM Model for Hate Detection—0
An Exploratory Study on Temporally Evolving Discussion around Covid-19 using Diachronic Word Embeddings—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
More Romanian word embeddings from the RETEROM project—0
Is Neural Topic Modelling Better than Clustering? An Empirical Study on Clustering with Contextual Embeddings for Topics—0
Learning and Evaluating Character Representations in Novels—0
On the interpretability and significance of bias metrics in texts: a PMI-based approach—0
Isomorphic Cross-lingual Embeddings for Low-Resource Languages—0
Detecting Unassimilated Borrowings in Spanish: An Annotated Corpus and Approaches to Modeling—0
Interpretable embeddings to understand computing careers—0
First Bilingual Word Embeddings for te reo Māori and English: Towards Code-switching Detection in a Low-resourced setting—0
Pre-training and Fine-tuning Neural Topic Model: A Simple yet Effective Approach to Incorporating External Knowledge—0
Non-Linear Relational Information Probing in Word Embeddings—0
Sentence Selection Strategies for Distilling Word Embeddings from BERT—0
SOS: Systematic Offensive Stereotyping Bias in Word Embeddings—0
Vec2Node: Self-training with Tensor Augmentation for Text Classification with Few Labels—0
Sense Embeddings are also Biased -- Evaluating Social Biases in Static and Contextualised Sense Embeddings—0
Looking Into the Black Box - How Are Idioms Processed in BERT?—0
Crossword: Estimating Unknown Embeddings using Cross Attention and Alignment Strategies—0
Multi-Stage Framework with Refinement based Point Set Registration for Unsupervised Bi-Lingual Word Alignment—0
Cross-lingual Word Embeddings in Hyperbolic Space—0
Discrete Wavelet Transform for Efficient Word Embeddings and Sentence Encoding—0
Softmax Bottleneck Makes Language Models Unable to Represent Multi-mode Word Distributions—0
Metaphor Detection for Low Resource Languages: From Zero-Shot to Few-Shot Learning in Middle High German—0
FeelsGoodMan: Inferring Semantics of Twitch Neologisms—0
Unsupervised Domain Adaptation with Contrastive Learning for Cross-domain Chinese NER—0
Evaluating Metrics for Bias in Word Embeddings—0
Explainable Semantic Space by Grounding Language to Vision with Cross-Modal Contrastive Learning—0
Keyphrase Extraction Using Neighborhood Knowledge Based on Word Embeddings—0
PESTO: Switching Point based Dynamic and Relative Positional Encoding for Code-Mixed LanguagesCode0
Automated PII Extraction from Social Media for Raising Privacy Awareness: A Deep Transfer Learning Approach—0
Training Cross-Lingual embeddings for Setswana and SepediCode0
Topic-aware latent models for representation learning on networks—0
SocialVec: Social Entity EmbeddingsCode0
POSHAN: Cardinal POS Pattern Guided Attention for News Headline Incongruence—0
Monitoring geometrical properties of word embeddings for detecting the emergence of new topics—0
My House, My Rules: Learning Tidying Preferences with Graph Neural Networks—0
Leveraging Advantages of Interactive and Non-Interactive Models for Vector-Based Cross-Lingual Information Retrieval—0
UnClE: Explicitly Leveraging Semantic Similarity to Reduce the Parameters of Word Embeddings—0
On the Cross-lingual Transferability of Contextualized Sense Embeddings—0
Named Entity Recognition in the Romanian Legal DomainCode0
Do not neglect related languages: The case of low-resource Occitan cross-lingual word embeddings—0
HOTTER: Hierarchical Optimal Topic Transport with Explanatory Context RepresentationsCode0
Decoding Word Embeddings with Brain-Based Semantic Features—0
Increasing Sentence-Level Comprehension Through Text Classification of Epistemic Functions—0
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