SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2751–2775 of 4002 papers

TitleStatusHype
UWB at SemEval-2018 Task 1: Emotion Intensity Detection in Tweets—0
Pruning Basic Elements for Better Automatic Evaluation of Summaries—0
What the Vec? Towards Probabilistically Grounded Embeddings—0
Multi-turn Dialogue Response Generation in an Adversarial Learning Framework—0
Quantum-inspired Complex Word Embedding—0
Unsupervised Alignment of Embeddings with Wasserstein ProcrustesCode0
Unsupervised detection of diachronic word sense evolution—0
Convolutional neural networks for chemical-disease relation extraction are improved with character-based word embeddings—0
UMDuluth-CS8761 at SemEval-2018 Task 9: Hypernym Discovery using Hearst Patterns, Co-occurrence frequencies and Word Embeddings—0
Lifelong Domain Word Embedding via Meta-LearningCode0
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling MechanismsCode0
Enhancing Chinese Intent Classification by Dynamically Integrating Character Features into Word Embeddings with Ensemble Techniques—0
How much does a word weigh? Weighting word embeddings for word sense induction—0
Scoring Lexical Entailment with a Supervised Directional Similarity NetworkCode0
Bilingual Sentiment Embeddings: Joint Projection of Sentiment Across LanguagesCode0
Morphosyntactic Tagging with a Meta-BiLSTM Model over Context Sensitive Token EncodingsCode0
Aff2Vec: Affect--Enriched Distributional Word Representations—0
Sentence Modeling via Multiple Word Embeddings and Multi-level Comparison for Semantic Textual Similarity—0
Unsupervised Cross-Modal Alignment of Speech and Text Embedding Spaces—0
A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddingsCode1
Simplifying Sentences with Sequence to Sequence Models—0
Unsupervised Learning of Style-sensitive Word Vectors—0
Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular MaximizationCode0
Effects of Word Embeddings on Neural Network-based Pitch Accent Detection—0
New Embedded Representations and Evaluation Protocols for Inferring Transitive Relations—0
Show:102550
← PrevPage 111 of 161Next →

No leaderboard results yet.