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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 2451–2500 of 4002 papers

TitleStatusHype
TopicThunder at SemEval-2017 Task 4: Sentiment Classification Using a Convolutional Neural Network with Distant Supervision—0
Topological Data Analysis for Word Sense Disambiguation—0
Topological Data Analysis in Text Classification: Extracting Features with Additive Information—0
Topology of Word Embeddings: Singularities Reflect Polysemy—0
Towards Automated Website Classification by Deep Learning—0
Toward Better Loanword Identification in Uyghur Using Cross-lingual Word Embeddings—0
Toward Better Storylines with Sentence-Level Language Models—0
Toward Incorporation of Relevant Documents in word2vec—0
Toward Interpretability of Dual-Encoder Models for Dialogue Response Suggestions—0
Toward Mention Detection Robustness with Recurrent Neural Networks—0
Toward Multilingual Identification of Online Registers—0
Towards a Gold Standard for Evaluating Danish Word Embeddings—0
Towards a Model of Prediction-based Syntactic Category Acquisition: First Steps with Word Embeddings—0
Towards a Semi-Automatic Detection of Reflexive and Reciprocal Constructions and Their Representation in a Valency Lexicon—0
Towards a Theoretical Understanding of Word and Relation Representation—0
Towards Augmenting Lexical Resources for Slang and African American English—0
Towards a Unified End-to-End Approach for Fully Unsupervised Cross-Lingual Sentiment Analysis—0
Towards a Universal Sentiment Classifier in Multiple languages—0
Towards Automating Healthcare Question Answering in a Noisy Multilingual Low-Resource Setting—0
Towards classification parity across cohorts—0
Towards Entity Spaces—0
Towards hate speech detection in low-resource languages: Comparing ASR to acoustic word embeddings on Wolof and Swahili—0
Towards High Accuracy Named Entity Recognition for Icelandic—0
Towards Lexical Chains for Knowledge-Graph-based Word Embeddings—0
Towards Lower Bounds on Number of Dimensions for Word Embeddings—0
Towards Optimal Transport with Global Invariances—0
Towards Qualitative Word Embeddings Evaluation: Measuring Neighbors Variation—0
Towards Resolving Word Ambiguity with Word Embeddings—0
Towards Smart Point-and-Shoot Photography—0
Towards the Understanding of Gaming Audiences by Modeling Twitch Emotes—0
Towards Unsupervised Text Classification Leveraging Experts and Word Embeddings—0
Toward Understanding Bias Correlations for Mitigation in NLP—0
Toward Word Embedding for Personalized Information Retrieval—0
TRAC-1 Shared Task on Aggression Identification: IIT(ISM)@COLING'18—0
Tracing armed conflicts with diachronic word embedding models—0
Tracing variation in discourse connectives in translation and interpreting through neural semantic spaces—0
Tracking Changes in ESG Representation: Initial Investigations in UK Annual Reports—0
Tracking Semantic Change in Cognate Sets for English and Romance Languages—0
Tracking the Evolution of Words with Time-reflective Text Representations—0
Tracking the progress of Language Models by extracting their underlying Knowledge Graphs—0
Traffic event description based on Twitter data using Unsupervised Learning Methods for Indian road conditions—0
Training and Evaluating Multimodal Word Embeddings with Large-scale Web Annotated Images—0
Training Word Sense Embeddings With Lexicon-based Regularization—0
Transcending the "Male Code": Implicit Masculine Biases in NLP Contexts—0
TransDrift: Modeling Word-Embedding Drift using Transformer—0
Transfer and Multi-Task Learning for Noun--Noun Compound Interpretation—0
Transfer Learning across Low-Resource, Related Languages for Neural Machine Translation—0
Transfer Learning in Natural Language Processing—0
Transferred Embeddings for Igbo Similarity, Analogy, and Diacritic Restoration Tasks—0
Transferring Coreference Resolvers with Posterior Regularization—0
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