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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/laura-burdick/embeddingStability

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Factors Influencing the Surprising Instability of Word Embeddings

https://github.com/laura-burdick/multilingual-stability

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Analyzing the Surprising Variability in Word Embedding Stability Across Languages

https://github.com/lgazpio/DAM_STS

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Uncovering divergent linguistic information in word embeddings with lessons for intrinsic and extrinsic evaluation

https://github.com/licstar/compare

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How to Generate a Good Word Embedding?

https://github.com/limorigu/Cockamamie-Gobbledegook

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Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops

https://github.com/limu-research/2024-edm-e2vec

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E2Vec: Feature Embedding with Temporal Information for Analyzing Student Actions in E-Book Systems

https://github.com/lina-luck/semantic_concept_embeddings

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Distilling Semantic Concept Embeddings from Contrastively Fine-Tuned Language Models

https://github.com/lirondos/coalas

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Detecting Unassimilated Borrowings in Spanish: An Annotated Corpus and Approaches to Modeling

https://github.com/livnlp/bias-sense

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Sense Embeddings are also Biased--Evaluating Social Biases in Static and Contextualised Sense Embeddings

https://github.com/livnlp/svp-dims

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Investigating the Contextualised Word Embedding Dimensions Specified for Contextual and Temporal Semantic Changes

https://github.com/livnlp/timeadapted-dcwe

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Learning Dynamic Contextualised Word Embeddings via Template-based Temporal Adaptation

https://github.com/locuslab/mixing

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The Mixing method: low-rank coordinate descent for semidefinite programming with diagonal constraints

https://github.com/long21wt/robust-bert-based-metrics

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Layer or Representation Space: What makes BERT-based Evaluation Metrics Robust?

https://github.com/lostkuma/GraphOfTweets

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Graph-of-Tweets: A Graph Merging Approach to Sub-event Identification

https://github.com/lsj2408/XLP

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Revisiting Language Encoding in Learning Multilingual Representations

https://github.com/ltgoslo/diachronic_armed_conflicts

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One-to-X analogical reasoning on word embeddings: a case for diachronic armed conflict prediction from news texts

https://github.com/lttam/sobolevtransport

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Sobolev Transport: A Scalable Metric for Probability Measures with Graph Metrics

https://github.com/lu-wo/quantifying-redundancy

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Quantifying the redundancy between prosody and text

https://github.com/lucabenedetto/qdet-comparison

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A quantitative study of NLP approaches to question difficulty estimation

https://github.com/lucy3/context_semantic_axes

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Discovering Differences in the Representation of People using Contextualized Semantic Axes

https://github.com/luohongyin/RGX

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Cooperative Self-training of Machine Reading Comprehension

https://github.com/luosx18/biomedical-sentence-aligner

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Sentence Alignment with Parallel Documents Facilitates Biomedical Machine Translation

https://github.com/luosx18/ued

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Semi-constraint Optimal Transport for Entity Alignment with Dangling Cases

https://github.com/machelreid/vcdm

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VCDM: Leveraging Variational Bi-encoding and Deep Contextualized Word Representations for Improved Definition Modeling

https://github.com/mainlp/codeswitchclir

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Boosting Zero-shot Cross-lingual Retrieval by Training on Artificially Code-Switched Data

https://github.com/majiangqin/Image-to-Recipe-Translation-using-AI

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Deep Image-to-Recipe Translation

https://github.com/malllabiisc/ConfGCN

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Neural Graph Embedding Methods for Natural Language Processing

https://github.com/malllabiisc/WordGCN

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Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks

https://github.com/mandarjoshi90/pair2vec

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pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference

https://github.com/mandt-lab/bayesian-ac

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Variational Bayesian Quantization

https://github.com/mandt-lab/vbq

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Variational Bayesian Quantization

https://github.com/marceaunahon/gpt_embeddings

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Strong and weak alignment of large language models with human values

https://github.com/marionbartl/gender-bias-BERT

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Unmasking Contextual Stereotypes: Measuring and Mitigating BERT's Gender Bias

https://github.com/mariru/dynamic_bernoulli_embeddings

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Dynamic Bernoulli Embeddings for Language Evolution

https://github.com/mariru/structured_embeddings

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Structured Embedding Models for Grouped Data

https://github.com/masoudjs/simalign

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SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings

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