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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 801–850 of 4002 papers

TitleStatusHype
Regional Differences in Information Privacy Concerns After the Facebook-Cambridge Analytica Data Scandal—0
An experimental study of the vision-bottleneck in VQA—0
Hindi/Bengali Sentiment Analysis Using Transfer Learning and Joint Dual Input Learning with Self AttentionCode0
Bench-Marking And Improving Arabic Automatic Image Captioning Through The Use Of Multi-Task Learning Paradigm—0
HistBERT: A Pre-trained Language Model for Diachronic Lexical Semantic AnalysisCode0
Fairness for Text Classification Tasks with Identity Information Data Augmentation Methods—0
L3Cube-MahaCorpus and MahaBERT: Marathi Monolingual Corpus, Marathi BERT Language Models, and Resources—0
Towards a Theoretical Understanding of Word and Relation Representation—0
Learning Representations of Entities and Relations—0
Recognition of Implicit Geographic Movement in Text—0
Taxonomy Enrichment with Text and Graph Vector Representations—0
Evaluating the timing and magnitude of semantic change in diachronic word embedding models—0
Regional Negative Bias in Word Embeddings Predicts Racial Animus--but only via Name Frequency—0
Automation of Citation Screening for Systematic Literature Reviews using Neural Networks: A Replicability StudyCode0
Evaluating Machine Common Sense via Cloze Testing—0
Tracking Legislators’ Expressed Policy Agendas in Real TimeCode0
Sectioning of Biomedical Abstracts: A Sequence of Sequence Classification Task—0
Modeling Tension in Stories via Commonsense Reasoning and Emotional Word Embeddings—0
Cooperative Self-training of Machine Reading Comprehension—0
Language Models for Code-switch Detection of te reo Māori and English in a Low-resource Setting—0
Topic Modeling with Topological Data Analysis—0
Minimally-Supervised Relation Induction from Pre-trained Language Model—0
Feasibility of BERT Embeddings For Domain-Specific Knowledge Mining—0
Don’t Forget Cheap Training Signals Before Building Unsupervised Bilingual Word Embeddings—0
Impart Contextualization to Static Word Embeddings through Semantic Relations—0
Revisiting Additive Compositionality: AND, OR, and NOT Operations with Word Embeddings—0
Addressing the Challenges of Cross-Lingual Hate Speech Detection—0
Compressing Word Embeddings Using Syllables—0
Diagnosing BERT with Retrieval HeuristicsCode0
D-Graph: AI-Assisted Design Concept Exploration Graph—0
Embeddings Evaluation Using a Novel Measure of Semantic SimilarityCode0
Applying Word Embeddings to Measure Valence in Information Operations Targeting Journalists in Brazil—0
Semi-automatic WordNet Linking using Word Embeddings—0
Predicting Influenza A Viral Host Using PSSM and Word Embeddings—0
Which Student is Best? A Comprehensive Knowledge Distillation Exam for Task-Specific BERT Models—0
"A Passage to India": Pre-trained Word Embeddings for Indian Languages—0
Traffic event description based on Twitter data using Unsupervised Learning Methods for Indian road conditions—0
Zero-shot and Few-shot Learning with Knowledge Graphs: A Comprehensive Survey—0
Joint Mitigation of Interactional Bias—0
Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource LanguagesCode0
Unsupervised Matching of Data and TextCode0
Identification of Biased Terms in News Articles by Comparison of Outlet-specific Word Embeddings—0
Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic Information PreservingCode0
Combining Textual Features for the Detection of Hateful and Offensive LanguageCode0
Few-Shot NLU with Vector Projection Distance and Abstract Triangular CRF—0
Emotion-Cause Pair Extraction in Customer Reviews—0
BERTMap: A BERT-based Ontology Alignment System—0
Inferring Prototypes for Multi-Label Few-Shot Image Classification with Word Vector Guided Attention—0
Sdutta at ComMA@ICON: A CNN-LSTM Model for Hate Detection—0
Retrofitting of Pre-trained Emotion Words with VAD-dimensions and the Plutchik Emotions—0
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