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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 901–925 of 4002 papers

TitleStatusHype
Neural Machine Translation for Tamil–Telugu Pair—0
Data-Driven Detection of General Chiasmi Using Lexical and Semantic FeaturesCode0
Common Sense Bias in Semantic Role LabelingCode0
Tracing variation in discourse connectives in translation and interpreting through neural semantic spaces—0
GiBERT: Enhancing BERT with Linguistic Information using a Lightweight Gated Injection MethodCode0
UnClE: Explicitly Leveraging Semantic Similarity to Reduce the Parameters of Word Embeddings—0
Distilling Word Meaning in Context from Pre-trained Language ModelsCode0
Monitoring geometrical properties of word embeddings for detecting the emergence of new topics.—0
Do not neglect related languages: The case of low-resource Occitan cross-lingual word embeddings—0
Word Equations: Inherently Interpretable Sparse Word Embeddings through Sparse Coding—0
Scaffolded input promotes atomic organization in the recurrent neural network language modelCode0
Is Stance Detection Topic-Independent and Cross-topic Generalizable? - A Reproduction Study—0
HOTTER: Hierarchical Optimal Topic Transport with Explanatory Context RepresentationsCode0
On the Cross-lingual Transferability of Contextualized Sense Embeddings—0
A Comprehensive Comparison of Word Embeddings in Event & Entity Coreference Resolution.Code0
Developing Conversational Data and Detection of Conversational Humor in Telugu—0
BAHP: Benchmark of Assessing Word Embeddings in Historical Portuguese—0
Locality Preserving Sentence Encoding—0
The Early Modern Dutch Mediascape. Detecting Media Mentions in Chronicles Using Word Embeddings and CRFCode0
Decoding Word Embeddings with Brain-Based Semantic Features—0
Learning Personal Food Preferences via Food Logs EmbeddingCode0
The Golden Rule as a Heuristic to Measure the Fairness of Texts Using Machine Learning—0
Word embeddings for topic modeling: an application to the estimation of the economic policy uncertainty index—0
Measuring a Texts Fairness Dimensions Using Machine Learning Based on Social Psychological Factors—0
Improving the Diversity of Unsupervised Paraphrasing with Embedding OutputsCode0
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