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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://github.com/thaleaschlender/An-Evaluation-of-Multiclass-Debiasing-Methods-on-Word-Embeddings

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"Thy algorithm shalt not bear false witness": An Evaluation of Multiclass Debiasing Methods on Word Embeddings

https://github.com/tharindudr/DeepOffense

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Multilingual Offensive Language Identification with Cross-lingual Embeddings

https://github.com/themody/debiasing-sentence-embedders-through-contrastive-word-pairs

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Debiasing Sentence Embedders through Contrastive Word Pairs

https://github.com/thespectrewithin/cross-lingual_NER

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Neural Cross-Lingual Named Entity Recognition with Minimal Resources

https://github.com/thunlp/SememePSO-Attack

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Word-level Textual Adversarial Attacking as Combinatorial Optimization

https://github.com/tiberiu44/TTS-Cube

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Generative Adversarial Training for Text-to-Speech Synthesis Based on Raw Phonetic Input and Explicit Prosody Modelling

https://github.com/tigerchen52/love

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Imputing Out-of-Vocabulary Embeddings with LOVE Makes Language Models Robust with Little Cost

https://github.com/timoschick/bertram

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BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performance

https://github.com/timoschick/form-context-model

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Learning Semantic Representations for Novel Words: Leveraging Both Form and Context

https://github.com/timotheemickus/codwoe

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IRB-NLP at SemEval-2022 Task 1: Exploring the Relationship Between Words and Their Semantic Representations

https://github.com/tjunlp-lab/CogAlign

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CogAlign: Learning to Align Textual Neural Representations to Cognitive Language Processing Signals

https://github.com/tnq177/improving_lexical_choice_in_nmt

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Improving Lexical Choice in Neural Machine Translation

https://github.com/tnq177/transformers_without_tears

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Transformers without Tears: Improving the Normalization of Self-Attention

https://github.com/tomekkorbak/treehopper

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Fine-tuning Tree-LSTM for phrase-level sentiment classification on a Polish dependency treebank. Submission to PolEval task 2

https://github.com/tommasoc80/Event_detection_CLiC-it2018

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Italian Event Detection Goes Deep Learning

https://github.com/toshohirasawa/nmtpytorch-emb-pred

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Multimodal Machine Translation with Embedding Prediction

https://github.com/trikaldarshi/ssl_awe

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Improving Acoustic Word Embeddings through Correspondence Training of Self-supervised Speech Representations

https://github.com/truas/LexicalChain_Builder

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Enhanced word embeddings using multi-semantic representation through lexical chains

https://github.com/truas/MSSA

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Multi-sense embeddings through a word sense disambiguation process

https://github.com/trungtrinh44/N-VAE

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Nested Variational Autoencoder for Topic Modeling on Microtexts with Word Vectors

https://github.com/tshi04/DMSC_FEDA

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An Interpretable and Uncertainty Aware Multi-Task Framework for Multi-Aspect Sentiment Analysis

https://github.com/tstafylakis/Lipreading-ResNet

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Deep word embeddings for visual speech recognition

https://github.com/tudarmstadt-lt/sensegram

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Making Sense of Word Embeddings

https://github.com/tugas-akhir-nlp/indonesian-coreference-resolution-cnn

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Coreference Resolution System for Indonesian Text with Mention Pair Method and Singleton Exclusion using Convolutional Neural Network

https://github.com/turkish-word-embeddings/word-embeddings-repository-for-turkish

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A Comprehensive Analysis of Static Word Embeddings for Turkish

https://github.com/tuur/WLLETlinkClassification

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Word-Level Loss Extensions for Neural Temporal Relation Classification

https://github.com/tuxworth/disinformation-insight-twitter

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Deriving Disinformation Insights from Geolocalized Twitter Callouts

https://github.com/twadada/lexsub_decontextualised

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Unsupervised Lexical Substitution with Decontextualised Embeddings

https://github.com/twadada/multilingual-nlm

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Learning Contextualised Cross-lingual Word Embeddings and Alignments for Extremely Low-Resource Languages Using Parallel Corpora

https://github.com/twelvelabs-io/video-embeddings-evaluation-framework

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TWLV-I: Analysis and Insights from Holistic Evaluation on Video Foundation Models

https://github.com/uber-research/parallax

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Parallax: Visualizing and Understanding the Semantics of Embedding Spaces via Algebraic Formulae

https://github.com/uclanlp/gn_glove

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Learning Gender-Neutral Word Embeddings

https://github.com/uclmr/emoji2vec

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emoji2vec: Learning Emoji Representations from their Description

https://github.com/uds-lsv/AWEs_phon_sim

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Do Acoustic Word Embeddings Capture Phonological Similarity? An Empirical Study

https://github.com/uds-lsv/noise-matrix-ner

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Feature-Dependent Confusion Matrices for Low-Resource NER Labeling with Noisy Labels

https://github.com/uds-lsv/semantically_enriched_awes

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Integrating Form and Meaning: A Multi-Task Learning Model for Acoustic Word Embeddings

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