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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 701–725 of 4002 papers

TitleStatusHype
On the interpretability and significance of bias metrics in texts: a PMI-based approach—0
Softmax Bottleneck Makes Language Models Unable to Represent Multi-mode Word Distributions—0
Vec2Node: Self-training with Tensor Augmentation for Text Classification with Few Labels—0
Crossword: Estimating Unknown Embeddings using Cross Attention and Alignment Strategies—0
SOS: Systematic Offensive Stereotyping Bias in Word Embeddings—0
Learning and Evaluating Character Representations in Novels—0
Looking Into the Black Box - How Are Idioms Processed in BERT?—0
Detecting Unassimilated Borrowings in Spanish: An Annotated Corpus and Approaches to Modeling—0
First Bilingual Word Embeddings for te reo Māori and English: Towards Code-switching Detection in a Low-resourced setting—0
Is Neural Topic Modelling Better than Clustering? An Empirical Study on Clustering with Contextual Embeddings for Topics—0
Multi-Stage Framework with Refinement based Point Set Registration for Unsupervised Bi-Lingual Word Alignment—0
Evaluating Metrics for Bias in Word Embeddings—0
Zero-Shot Learning in Named-Entity Recognition with External KnowledgeCode1
Keyphrase Extraction Using Neighborhood Knowledge Based on Word Embeddings—0
Explainable Semantic Space by Grounding Language to Vision with Cross-Modal Contrastive Learning—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
Monitoring geometrical properties of word embeddings for detecting the emergence of new topics—0
On the Impact of Temporal Representations on Metaphor DetectionCode1
POSHAN: Cardinal POS Pattern Guided Attention for News Headline Incongruence—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
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