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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 3951–4000 of 4002 papers

TitleStatusHype
Feature Embedding for Dependency Parsing—0
Feature Engineering vs BERT on Twitter Data—0
Feelings from the Past---Adapting Affective Lexicons for Historical Emotion Analysis—0
FeelsGoodMan: Inferring Semantics of Twitch Neologisms—0
FeelsGoodMan: Inferring Semantics of Twitch Neologisms—0
Fermi at SemEval-2017 Task 7: Detection and Interpretation of Homographic puns in English Language—0
Few-Shot NLU with Vector Projection Distance and Abstract Triangular CRF—0
Field Embedding: A Unified Grain-Based Framework for Word Representation—0
Figure Eight at SemEval-2019 Task 3: Ensemble of Transfer Learning Methods for Contextual Emotion Detection—0
Figure Me Out: A Gold Standard Dataset for Metaphor Interpretation—0
Finding Individual Word Sense Changes and their Delay in Appearance—0
Finding People's Professions and Nationalities Using Distant Supervision - The FMI@SU "goosefoot" team at the WSDM Cup 2017 Triple Scoring Task—0
Fine-Grained Contextual Predictions for Hard Sentiment Words—0
Fine-grained Opinion Mining with Recurrent Neural Networks and Word Embeddings—0
Finely Tuned, 2 Billion Token Based Word Embeddings for Portuguese—0
Fine-tuning BERT to classify COVID19 tweets containing symptoms—0
Finki at SemEval-2016 Task 4: Deep Learning Architecture for Twitter Sentiment Analysis—0
Firearms and Tigers are Dangerous, Kitchen Knives and Zebras are Not: Testing whether Word Embeddings Can Tell—0
First Bilingual Word Embeddings for te reo Māori and English: Towards Code-switching Detection in a Low-resourced setting—0
Fitting Semantic Relations to Word Embeddings—0
FKIE_itf_2021 at CASE 2021 Task 1: Using Small Densely Fully Connected Neural Nets for Event Detection and Clustering—0
Flexible and Scalable State Tracking Framework for Goal-Oriented Dialogue Systems—0
FlorUniTo@TRAC-2: Retrofitting Word Embeddings on an Abusive Lexicon for Aggressive Language Detection—0
fMRI Semantic Category Decoding using Linguistic Encoding of Word Embeddings—0
Focusing Knowledge-based Graph Argument Mining via Topic Modeling—0
Fortia-FBK at SemEval-2017 Task 5: Bullish or Bearish? Inferring Sentiment towards Brands from Financial News Headlines—0
FRAQUE: a FRAme-based QUEstion-answering system for the Public Administration domain—0
French Contextualized Word-Embeddings with a sip of CaBeRnet: a New French Balanced Reference Corpus—0
Frequency-aware Dimension Selection for Static Word Embedding by Mixed Product Distance—0
Frequency-based Distortions in Contextualized Word Embeddings—0
From cart to truck: meaning shift through words in English in the last two centuries—0
From communities to interpretable network and word embedding: an unified approach—0
From Image to Text Classification: A Novel Approach based on Clustering Word Embeddings—0
From Language to Language-ish: How Brain-Like is an LSTM's Representation of Nonsensical Language Stimuli?—0
From meaning to perception -- exploring the space between word and odor perception embeddings—0
From Prejudice to Parity: A New Approach to Debiasing Large Language Model Word Embeddings—0
From Raw Text to Universal Dependencies - Look, No Tags!—0
From Word Vectors to Multimodal Embeddings: Techniques, Applications, and Future Directions For Large Language Models—0
From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers—0
From Zero to Hero: On the Limitations of Zero-Shot Language Transfer with Multilingual Transformers—0
Fully Delexicalized Contexts for Syntax-Based Word Embeddings—0
funSentiment at SemEval-2017 Task 4: Topic-Based Message Sentiment Classification by Exploiting Word Embeddings, Text Features and Target Contexts—0
funSentiment at SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs Using Word Vectors Built from StockTwits and Twitter—0
Fusing Vector Space Models for Domain-Specific Applications—0
Fusion approaches for emotion recognition from speech using acoustic and text-based features—0
ScoreGAN: A Fraud Review Detector based on Multi Task Learning of Regulated GAN with Data Augmentation—0
Gender and Racial Stereotype Detection in Legal Opinion Word Embeddings—0
Gender bias Evaluation in Luganda-English Machine Translation—0
Gender Bias Hidden Behind Chinese Word Embeddings: The Case of Chinese Adjectives—0
Gender Bias in Word Embeddings: A Comprehensive Analysis of Frequency, Syntax, and Semantics—0
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