https://github.com/gcollell/spatial-commonsense
공식 코드Acquiring Common Sense Spatial Knowledge through Implicit Spatial Templates
Papers with Code 아카이브
Word Embeddings
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 4
- 평가표
- 0
- 보존된 평가 기록
- 0
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/gedeonmate/hungarian_static_embeddings
공식 코드A Comparative Analysis of Static Word Embeddings for Hungarian
https://github.com/genggengcss/OntoZSL
공식 코드https://github.com/gentaiscool/meta-emb
공식 코드Hierarchical Meta-Embeddings for Code-Switching Named Entity Recognition
https://github.com/gguinet/semisupervised-alignement
공식 코드https://github.com/gguinet/semisupervised-alignment
공식 코드https://github.com/gimpong/AAAI21-WSDHQ
공식 코드Weakly Supervised Deep Hyperspherical Quantization for Image Retrieval
https://github.com/githublucheng/implementation-of-josec-coling-22
공식 코드https://github.com/gkaramanolakis/ISWD
공식 코드https://github.com/gkuling/birads_bert
공식 코드BI-RADS BERT & Using Section Segmentation to Understand Radiology Reports
https://github.com/glaciohound/lm-steer
공식 코드https://github.com/glnmario/cwr4lsc
공식 코드Analysing Lexical Semantic Change with Contextualised Word Representations
https://github.com/gmichalo/UmlsBERT
공식 코드https://github.com/gonenhila/gender_bias_lipstick
공식 코드https://github.com/gonenhila/grammatical_gender
공식 코드How does Grammatical Gender Affect Noun Representations in Gender-Marking Languages?
https://github.com/gonenhila/usage_change
공식 코드Simple, Interpretable and Stable Method for Detecting Words with Usage Change across Corpora
https://github.com/google-research/google-research
공식 코드Toward Better Storylines with Sentence-Level Language Models
https://github.com/google-research/retvec
공식 코드https://github.com/goru001/inltk
공식 코드https://github.com/gsasikiran/Comparative-Evaluation-of-Pretrained-Transfer-Learning-Models-on-ASAG
공식 코드Comparative Evaluation of Pretrained Transfer Learning Models on Automatic Short Answer Grading
https://github.com/gucorpling/discodisco
공식 코드https://github.com/guillemram97/wp-hungarian
공식 코드On a Novel Application of Wasserstein-Procrustes for Unsupervised Cross-Lingual Learning
https://github.com/guolinke/TUPE
공식 코드https://github.com/guoyinwang/EMBDA
공식 코드https://github.com/guyrosin/generating_timelines
공식 코드https://github.com/gwohlgen/thai_word_similarity
공식 코드Word Similarity Datasets for Thai: Construction and Evaluation
https://github.com/h-aldarmaki/acoustic_embeddings
공식 코드Supervised Acoustic Embeddings And Their Transferability Across Languages
https://github.com/h-aldarmaki/sent_translation_retrieval
공식 코드https://github.com/hadi-abdine/WordEmbeddingsEvalFLUE
공식 코드Evaluation Of Word Embeddings From Large-Scale French Web Content
https://github.com/hadyelsahar/relation-discovery-2-entities
공식 코드https://github.com/hallerp/dyslexia-seqmod
공식 코드https://github.com/halnegheimish/forcedinvalidation
공식 코드Towards preserving word order importance through Forced Invalidation
https://github.com/hanselowski/embedding_decomp
공식 코드Analyzing Structures in the Semantic Vector Space: A Framework for Decomposing Word Embeddings
https://github.com/harsh19/SPINE
공식 코드https://github.com/haseebs/OWE
공식 코드An Open-World Extension to Knowledge Graph Completion Models
https://github.com/hassiahk/MLRC-2020-Double-Hard-Debias
공식 코드[RE] Double-Hard Debias: Tailoring Word Embeddings for Gender Bias Mitigation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.