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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 1901–1950 of 4002 papers

TitleStatusHype
Initial Experiments in Data-Driven Morphological Analysis for Finnish—0
Injecting Wiktionary to improve token-level contextual representations using contrastive learning—0
“Are you calling for the vaporizer you ordered?” Combining Search and Prediction to Identify Orders in Contact Centers—0
Inline Detection of Domain Generation Algorithms with Context-Sensitive Word Embeddings—0
Exact gradient updates in time independent of output size for the spherical loss family—0
Evolving Large Text Corpora: Four Versions of the Icelandic Gigaword Corpus—0
Clinical Abbreviation Disambiguation Using Neural Word Embeddings—0
Evolving Hate Speech Online: An Adaptive Framework for Detection and Mitigation—0
Clickbait detection using word embeddings—0
Inspecting the concept knowledge graph encoded by modern language models—0
Instantiation—0
Integrating Dictionary Feature into A Deep Learning Model for Disease Named Entity Recognition—0
Integrating Distributional Lexical Contrast into Word Embeddings for Antonym-Synonym Distinction—0
Are Word Embeddings Really a Bad Fit for the Estimation of Thematic Fit?—0
Alzheimer Disease Classification through ASR-based Transcriptions: Exploring the Impact of Punctuation and Pauses—0
Integrating Pause Information with Word Embeddings in Language Models for Alzheimer's Disease Detection from Spontaneous Speech—0
Integrating Reviews into Personalized Ranking for Cold Start Recommendation—0
Event Role Labelling using a Neural Network Model (\'Etiquetage en r\^oles \'ev\'enementiels fond\'e sur l'utilisation d'un mod\`ele neuronal) [in French]—0
Event Role Extraction using Domain-Relevant Word Representations—0
CLFD: A Novel Vectorization Technique and Its Application in Fake News Detection—0
Integrating Topic Modeling with Word Embeddings by Mixtures of vMFs—0
Integration of Domain Knowledge using Medical Knowledge Graph Deep Learning for Cancer Phenotyping—0
Event Prominence Extraction Combining a Knowledge-Based Syntactic Parser and a BERT Classifier for Dutch—0
Event Ordering with a Generalized Model for Sieve Prediction Ranking—0
Interactive Re-Fitting as a Technique for Improving Word Embeddings—0
CLCL (Geneva) DINN Parser: a Neural Network Dependency Parser Ten Years Later—0
Are Word Embedding-based Features Useful for Sarcasm Detection?—0
Interpretable Adversarial Training for Text—0
Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts—0
Interpretable embeddings to understand computing careers—0
Interpretable Neural Embeddings with Sparse Self-Representation—0
Event extraction from Twitter using Non-Parametric Bayesian Mixture Model with Word Embeddings—0
Event Detection Using Frame-Semantic Parser—0
Interpretable Word Embeddings via Informative Priors—0
Classifying Text-Based Conspiracy Tweets related to COVID-19 using Contextualized Word Embeddings—0
Interpreting Pretrained Contextualized Representations via Reductions to Static Embeddings—0
Classifying Semantic Clause Types: Modeling Context and Genre Characteristics with Recurrent Neural Networks and Attention—0
Interpreting Word-Level Hidden State Behaviour of Character-Level LSTM Language Models—0
A LSTM Approach with Sub-Word Embeddings for Mongolian Phrase Break Prediction—0
Inter-Weighted Alignment Network for Sentence Pair Modeling—0
Evaluation of Word Embeddings for the Social Sciences—0
Intrinsic Bias Metrics Do Not Correlate with Application Bias—0
Intrinsic Evaluations of Word Embeddings: What Can We Do Better?—0
Intrinsic Image Captioning Evaluation—0
Evaluation of word embeddings against cognitive processes: primed reaction times in lexical decision and naming tasks—0
Evaluation of Taxonomy Enrichment on Diachronic WordNet Versions—0
Introducing Syllable Tokenization for Low-resource Languages: A Case Study with Swahili—0
Invariance and identifiability issues for word embeddings—0
InvBERT: Reconstructing Text from Contextualized Word Embeddings by inverting the BERT pipeline—0
Evaluation of Stacked Embeddings for Bulgarian on the Downstream Tasks POS and NERC—0
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