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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/czyssrs/GloREPlus
공식 코드Global Textual Relation Embedding for Relational Understanding
https://github.com/d-gurgurov/GrEmLIn-Green-Embeddings-LRLs
공식 코드https://github.com/danielchyeh/this-is-my
공식 코드Meta-Personalizing Vision-Language Models to Find Named Instances in Video
https://github.com/danifg/SemanticPointer
공식 코드Transition-based Semantic Dependency Parsing with Pointer Networks
https://github.com/danlou/LMMS
공식 코드https://github.com/dannysvof/SUAEx
공식 코드https://github.com/datexis/comply
공식 코드Comply: Learning Sentences with Complex Weights inspired by Fruit Fly Olfaction
https://github.com/davidmatthews1uvm/2019-IROS
공식 코드Word2vec to behavior: morphology facilitates the grounding of language in machines
https://github.com/davidtpeng/sensory-spaces-perceptual-verbs
공식 코드Exploring the Sensory Spaces of English Perceptual Verbs in Natural Language Data
https://github.com/dbamman/geoSGLM
공식 코드https://github.com/dbamman/latin-bert
공식 코드Latin BERT: A Contextual Language Model for Classical Philology
https://github.com/dd1497/cro-diachronic-emb
공식 코드Characterizing Linguistic Shifts in Croatian News via Diachronic Word Embeddings
https://github.com/deezer/MultilingualMusicGenreEmbedding
공식 코드Multilingual Music Genre Embeddings for Effective Cross-Lingual Music Item Annotation
https://github.com/deezer/w2v_reco_hyperparameters_matter
공식 코드https://github.com/dinghanshen/SWEM
공식 코드Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms
https://github.com/dingwc/multisense
공식 코드https://github.com/dipteshkanojia/challengeCognateFF
공식 코드Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource Languages
https://github.com/divamgupta/mttdsc
공식 코드Multi-task Learning for Target-dependent Sentiment Classification
https://github.com/divyakoyy/codenames
공식 코드https://github.com/dmollaaliod/bioasq8b-public
공식 코드Query Focused Multi-document Summarisation of Biomedical Texts
https://github.com/drgriffis/Extrinsic-Evaluation-tasks
공식 코드Characterizing the impact of geometric properties of word embeddings on task performance
https://github.com/drgriffis/NeuralVecmap
공식 코드https://github.com/dsfsi/embedding-eval-data
공식 코드https://github.com/dsfsi/za-isizulu-siswati-news-2022
공식 코드https://github.com/dustalov/watset
공식 코드Watset: Automatic Induction of Synsets from a Graph of Synonyms
https://github.com/duyetdev/skill2vec-dataset
공식 코드Skill2vec: Machine Learning Approach for Determining the Relevant Skills from Job Description
https://github.com/dv-fenix/sylstm
공식 코드https://github.com/dylangrosz/Automatic_Detection_of_Sexist_Statements_Commonly_Used_at_the_Workplace
공식 코드Automatic Detection of Sexist Statements Commonly Used at the Workplace
https://github.com/easonnie/multiNLI_encoder
공식 코드Shortcut-Stacked Sentence Encoders for Multi-Domain Inference
https://github.com/ebrahimfeghhi/beyond-brainscore
공식 코드What Are Large Language Models Mapping to in the Brain? A Case Against Over-Reliance on Brain Scores
https://github.com/edilsonacjr/semeval2017
공식 코드NILC-USP at SemEval-2017 Task 4: A Multi-view Ensemble for Twitter Sentiment Analysis
https://github.com/eduard6421/ronli
공식 코드https://github.com/ehsansherkat/ConVec
공식 코드https://github.com/elena-apostol/simplex
공식 코드https://github.com/elmurod1202/crosLingWordEmbTurk
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.