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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

Showing 33013325 of 4002 papers

TitleStatusHype
Brundlefly at SemEval-2016 Task 12: Recurrent Neural Networks vs. Joint Inference for Clinical Temporal Information Extraction0
Brundlefly at SemEval-2016 Task 12: Recurrent Neural Networks vs. Joint Inference for Clinical Temporal Information Extraction0
BUCC 2017 Shared Task: a First Attempt Toward a Deep Learning Framework for Identifying Parallel Sentences in Comparable Corpora0
BUCC2020: Bilingual Dictionary Induction using Cross-lingual Embedding0
Building a Monolingual Parallel Corpus for Text Simplification Using Sentence Similarity Based on Alignment between Word Embeddings0
Building a robust sentiment lexicon with (almost) no resource0
Building a Web-Scale Dependency-Parsed Corpus from CommonCrawl0
Building Robust Spoken Language Understanding by Cross Attention between Phoneme Sequence and ASR Hypothesis0
Building Semantic Grams of Human Knowledge0
Building Sense Representations in Danish by Combining Word Embeddings with Lexical Resources0
Building Vision-Language Models on Solid Foundations with Masked Distillation0
Building Web-Interfaces for Vector Semantic Models with the WebVectors Toolkit0
BUSEM at SemEval-2017 Task 4A Sentiment Analysis with Word Embedding and Long Short Term Memory RNN Approaches0
Can AI Generate Love Advice?: Toward Neural Answer Generation for Non-Factoid Questions0
Can Domain Adaptation be Handled as Analogies?0
Can Existing Methods Debias Languages Other than English? First Attempt to Analyze and Mitigate Japanese Word Embeddings0
Can Eye Movement Data Be Used As Ground Truth For Word Embeddings Evaluation?0
Captioning Images with Novel Objects via Online Vocabulary Expansion0
Capturing Pragmatic Knowledge in Article Usage Prediction using LSTMs0
Card-660: Cambridge Rare Word Dataset - a Reliable Benchmark for Infrequent Word Representation Models0
Case Studies on using Natural Language Processing Techniques in Customer Relationship Management Software0
CAST: Corpus-Aware Self-similarity Enhanced Topic modelling0
Casteism in India, but Not Racism - a Study of Bias in Word Embeddings of Indian Languages0
Positional Artefacts Propagate Through Masked Language Model Embeddings0
應用詞向量於語言樣式探勘之研究 (Mining Language Patterns Using Word Embeddings) [In Chinese]0
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