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Word Embeddings

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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.

<span style="color:grey; opacity: 0.6">( Image credit: Dynamic Word Embedding for Evolving Semantic Discovery )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://bitbucket.org/TomKenter/siamese-cbow

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Siamese CBOW: Optimizing Word Embeddings for Sentence Representations

https://bitbucket.org/aumc-kik/prompt_tuning_cancer_prediction

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Soft-prompt tuning to predict lung cancer using primary care free-text Dutch medical notes

https://bitbucket.org/bedizel/moe

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Misspelling Oblivious Word Embeddings

https://bitbucket.org/dascim/acl2018_abssumm

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Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular Maximization

https://bitbucket.org/gg42554/cl-sts

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A Resource-Light Method for Cross-Lingual Semantic Textual Similarity

https://bitbucket.org/luisespinosa/seven

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SeVeN: Augmenting Word Embeddings with Unsupervised Relation Vectors

https://bitbucket.org/nlpitu/xnli

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Baselines and test data for cross-lingual inference

https://bitbucket.org/robvanderg/monoise

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MoNoise: Modeling Noise Using a Modular Normalization System

https://bitbucket.org/robvanderg/w2v

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Fair is Better than Sensational:Man is to Doctor as Woman is to Doctor

https://bitbucket.org/shihaoji/wordrank

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WordRank: Learning Word Embeddings via Robust Ranking

https://github.com/4mekki4/promap

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ProMap: Effective Bilingual Lexicon Induction via Language Model Prompting

https://github.com/Activeyixiao/topic-specific-vector

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Deriving Word Vectors from Contextualized Language Models using Topic-Aware Mention Selection

https://github.com/Adaxry/GCDT

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GCDT: A Global Context Enhanced Deep Transition Architecture for Sequence Labeling

https://github.com/AdeDZY/SIGIR19-BERT-IR

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Deeper Text Understanding for IR with Contextual Neural Language Modeling

https://github.com/Aditi138/Embeddings

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Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representations

https://github.com/Akshitaag/Sarcasm_Detection

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"Did you really mean what you said?" : Sarcasm Detection in Hindi-English Code-Mixed Data using Bilingual Word Embeddings

https://github.com/AlanAnsell/PolyLM

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PolyLM: Learning about Polysemy through Language Modeling

https://github.com/AleT-Cig/DependencySyntax_DeepIrony

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Multilingual Irony Detection with Dependency Syntax and Neural Models

https://github.com/AlexMoreo/word-class-embeddings

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Word-Class Embeddings for Multiclass Text Classification

https://github.com/AmrMehasseb/Embeddings-finetuning

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A Simple and Effective Approach for Fine Tuning Pre-trained Word Embeddings for Improved Text Classification

https://github.com/Andy-jqa/bioelmo

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Probing Biomedical Embeddings from Language Models

https://github.com/Antimalweb/URLNet

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URLNet: Learning a URL Representation with Deep Learning for Malicious URL Detection

https://github.com/BFH-AMI/BIAS

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The BIAS Detection Framework: Bias Detection in Word Embeddings and Language Models for European Languages

https://github.com/Babylonpartners/corrsim

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Correlations between Word Vector Sets

https://github.com/Babylonpartners/fuzzymax

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Don't Settle for Average, Go for the Max: Fuzzy Sets and Max-Pooled Word Vectors

https://github.com/BatoolHamawi/COVID-19WordEmbeddings

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Eating Garlic Prevents COVID-19 Infection: Detecting Misinformation on the Arabic Content of Twitter

https://github.com/BinWang28/Sentence-Embedding-S3E

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Efficient Sentence Embedding via Semantic Subspace Analysis

https://github.com/BoChenGroup/WeTe

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Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings

https://github.com/BorisMuzellec/SubspaceOT

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Subspace Detours: Building Transport Plans that are Optimal on Subspace Projections

https://github.com/ChengyueGongR/FrequencyAgnostic

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FRAGE: Frequency-Agnostic Word Representation

https://github.com/CoNexDat/mw2v

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Learning language variations in news corpora through differential embeddings

https://github.com/DLYuanGod/RPN

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RPN: A Word Vector Level Data Augmentation Algorithm in Deep Learning for Language Understanding

https://github.com/DS3Lab/cognival

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CogniVal: A Framework for Cognitive Word Embedding Evaluation

https://github.com/DannyMerkx/caption2image

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Learning semantic sentence representations from visually grounded language without lexical knowledge

https://github.com/DannyMerkx/speech2image

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Seeing the advantage: visually grounding word embeddings to better capture human semantic knowledge

https://github.com/Deloris-NLP/CRNTM

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Context Reinforced Neural Topic Modeling over Short Texts

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