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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/joelmoniz/BLISS

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Bilingual Lexicon Induction with Semi-supervision in Non-Isometric Embedding Spaces

https://github.com/john-hewitt/conditional-probing

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Conditional probing: measuring usable information beyond a baseline

https://github.com/johnaot/Emotion_Semantic_Change

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Evolution of emotion semantics

https://github.com/johntailor/bertsenclu

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Efficient and Flexible Topic Modeling using Pretrained Embeddings and Bag of Sentences

https://github.com/johntiger1/multimodal_fairness

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Exploring Text Specific and Blackbox Fairness Algorithms in Multimodal Clinical NLP

https://github.com/joisino/anchor-energy

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Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces

https://github.com/joisino/wordtour

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Word Tour: One-dimensional Word Embeddings via the Traveling Salesman Problem

https://github.com/jowagner/mtb-tri-training

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Revisiting Tri-training of Dependency Parsers

https://github.com/jowagner/ud-combination

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Revisiting Tri-training of Dependency Parsers

https://github.com/jslin/LARQS

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An Evaluation Dataset for Legal Word Embedding: A Case Study On Chinese Codex

https://github.com/judicaelpoumay/event_entity_coref_ecb_plus

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A Comprehensive Comparison of Word Embeddings in Event & Entity Coreference Resolution

https://github.com/kamperh/globalphone_awe

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Multilingual acoustic word embedding models for processing zero-resource languages

https://github.com/kamperh/recipe_swbd_wordembeds

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Deep convolutional acoustic word embeddings using word-pair side information

https://github.com/kanekomasahiro/context-debias

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Debiasing Pre-trained Contextualised Embeddings

https://github.com/kanekomasahiro/dict-debias

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Dictionary-based Debiasing of Pre-trained Word Embeddings

https://github.com/kanekomasahiro/gp_debias

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Gender-preserving Debiasing for Pre-trained Word Embeddings

https://github.com/kata-ai/id-word2vec

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KaWAT: A Word Analogy Task Dataset for Indonesian

https://github.com/kata-ai/kawat

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KaWAT: A Word Analogy Task Dataset for Indonesian

https://github.com/katbailey/few-shot-text-classification

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Few-Shot Text Classification with Pre-Trained Word Embeddings and a Human in the Loop

https://github.com/kdrl/SCNE

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Segmentation-free Compositional $n$-gram Embedding

https://github.com/kellymarchisio/euc-v-graph-bli

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An Analysis of Euclidean vs. Graph-Based Framing for Bilingual Lexicon Induction from Word Embedding Spaces

https://github.com/kennethlimjf/contrastive-learning-in-distilled-models

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Contrastive Learning in Distilled Models

https://github.com/kennyjoseph/embedding_impressions

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When do Word Embeddings Accurately Reflect Surveys on our Beliefs About People?

https://github.com/kiyama-hajime/acss-simmat

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Analyzing Continuous Semantic Shifts with Diachronic Word Similarity Matrices

https://github.com/kmccurdy/w2v-gender

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Grammatical gender associations outweigh topical gender bias in crosslinguistic word embeddings

https://github.com/koc-lab/imparting-interpretability

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Imparting Interpretability to Word Embeddings while Preserving Semantic Structure

https://github.com/koclab/imparting-interpretability

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Imparting Interpretability to Word Embeddings while Preserving Semantic Structure

https://github.com/kumar-shridhar/Know-Your-Intent

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Subword Semantic Hashing for Intent Classification on Small Datasets

https://github.com/kylie-box/word_prisms

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Learning Efficient Task-Specific Meta-Embeddings with Word Prisms

https://github.com/l-bg/llms_brain_lateralization

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fMRI predictors based on language models of increasing complexity recover brain left lateralization

https://github.com/l3cube-pune/MarathiNLP

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L3Cube-MahaCorpus and MahaBERT: Marathi Monolingual Corpus, Marathi BERT Language Models, and Resources

https://github.com/lancopku/Embedding-Poisoning

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Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models

https://github.com/lancopku/WEAN

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Query and Output: Generating Words by Querying Distributed Word Representations for Paraphrase Generation

https://github.com/landiisotta/convae_architecture

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Deep Representation Learning of Electronic Health Records to Unlock Patient Stratification at Scale

https://github.com/lateral/minkowski

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Skip-gram word embeddings in hyperbolic space

https://github.com/laugustyniak/aspect_extraction

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Aspect Detection using Word and Char Embeddings with (Bi)LSTM and CRF

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