https://github.com/qq345736500/sarcasm
emoji2vec: Learning Emoji Representations from their Description
Papers with Code 아카이브
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/radoslawkrolikowski/sentiment-analysis-pytorch
Supervised Learning of Universal Sentence Representations from Natural Language Inference Data
https://github.com/ragerri/basque-embeddings-lrec2020
Give your Text Representation Models some Love: the Case for Basque
https://github.com/rajatgermany/qa-nlp
Supervised Learning of Universal Sentence Representations from Natural Language Inference Data
https://github.com/ridouaneg/Sinkhorn-Embeddings-MNIST
https://github.com/rightlit/cycle-image-gan-rev
https://github.com/rikhuijzer/nlu_datasets
https://github.com/ringbdstack/socialed
Transferring Knowledge Distillation for Multilingual Social Event Detection
https://github.com/rmenegaux/fastDNA
https://github.com/rockandroll123/natural-language-inference
Supervised Learning of Universal Sentence Representations from Natural Language Inference Data
https://github.com/romanows/sdoh-n2c2
The 2022 n2c2/UW Shared Task on Extracting Social Determinants of Health
https://github.com/romik9999/fasttext-1925f09ed3
https://github.com/rowanhm/counterfactual-data-substitution
https://github.com/rpryzant/causal-bert-pytorch
https://github.com/runqitian/CR-CNN
Classifying Relations by Ranking with Convolutional Neural Networks
https://github.com/rvstraalen/doc2vec-workshop
https://github.com/s1879281/Lexical-NMT
https://github.com/sabetAI/bucc-eval
https://github.com/sajidahmed12/CSE495-NLP-Assignment-Unsupervised-Neural-Machine-Translation
https://github.com/saleiro/SemEval2017-Task5
https://github.com/samnguyen8991/Facebook-MUSE
https://github.com/sathvikn/word_embedding_bias
https://github.com/satwikkottur/VisualWord2Vec
Visual Word2Vec (vis-w2v): Learning Visually Grounded Word Embeddings Using Abstract Scenes
https://github.com/saurabhrathor/InceptionModel_SentimentAnalysis
BB_twtr at SemEval-2017 Task 4: Twitter Sentiment Analysis with CNNs and LSTMs
https://github.com/sb-b/steps-parser
https://github.com/sebastian-hofstaetter/transformer-kernel-ranking
Interpretable & Time-Budget-Constrained Contextualization for Re-Ranking
https://github.com/selimseker/logogram-language-generator
https://github.com/serenera/Serenera
https://github.com/seunghwan1228/ELMO
Evaluation of sentence embeddings in downstream and linguistic probing tasks
https://github.com/sgrvinod/a-PyTorch-Tutorial-to-Sequence-Labeling
Empower Sequence Labeling with Task-Aware Neural Language Model
https://github.com/shaanchandra/InferSent
Supervised Learning of Universal Sentence Representations from Natural Language Inference Data
https://github.com/shakimov/SimpleQA-NER
https://github.com/shaneding/bilm-tf-experimentation
Evaluation of sentence embeddings in downstream and linguistic probing tasks
https://github.com/shaoyent/multimodal-elmo
https://github.com/shayanray/ApplyingCommonSense
ConceptNet 5.5: An Open Multilingual Graph of General Knowledge
https://github.com/shelleyHLX/bilm_EMLo
Evaluation of sentence embeddings in downstream and linguistic probing tasks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.