https://github.com/HeyLynne/char_cnn
Character-level Convolutional Networks for Text Classification
Papers with Code 아카이브
Text Classification
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Text Classification is the task of assigning a sentence or document an appropriate category. The categories depend on the chosen dataset and can range from topics.
Text Classification problems include emotion classification, news classification, citation intent classification, among others. Benchmark datasets for evaluating text classification capabilities include GLUE, AGNews, among others.
In recent years, deep learning techniques like XLNet and RoBERTa have attained some of the biggest performance jumps for text classification problems.
<span style="color:grey; opacity: 0.6">( Image credit: Text Classification Algorithms: A Survey )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Hibb-bb/ALLM
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Hironsan/anago
https://github.com/HoganZhang/pygcn_python3
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/Holldean/BERT-Pruning
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/HongyangGao/hConv-gPool-Net
Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations
https://github.com/HuihuiChyan/BJTUNLP_Practice2020
https://github.com/HuihuiChyan/BJTUNLP_Practice2021
https://github.com/IBM/MAX-Question-Answering
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/IBM/MAX-Text-Sentiment-Classifier
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/IBM/MAX-Toxic-Comment-Classifier
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/IIEKES/cbert_aug
https://github.com/IIEKES/cbert_aug_deprecated
https://github.com/IMPLabUniPr/UniParma-at-semeval-2021-task-5
https://github.com/IllinoisGraphBenchmark/IGB-Datasets
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/Impavidity/relogic
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/IndicoDataSolutions/finetune
https://github.com/InstituteForIndustrialEconomics/trac2
https://github.com/JA-Bar/nlp-depression
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/JHart96/keras_elmo_embedding_layer
https://github.com/JIRUWANG1997/top67-solution-for-Jigsaw-Unintended-Bias-in-Toxicity-Classification
Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification
https://github.com/JMSaindon/NlpSquad
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/JNUpython/bert
https://github.com/Jackma3/NER-Bert-BiLstm
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/JacobLau0513/676-MBTI
https://github.com/JakubStefko/w2vf
https://github.com/Jarvx/text-classification-pytorch
https://github.com/Jason-J-Choi/DeBERTa_TxtClassifier
https://github.com/JeheonPark596/sentimentsurvival
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/JerryKwon/melon_plylst_continuation
Taming Pretrained Transformers for Extreme Multi-label Text Classification
https://github.com/Jerryten/model_nlp
https://github.com/JiachuanDENG/CNN-Textual-RegressionModel-for-commodity-price-prediction
https://github.com/JiachuanDENG/Pytorch-CNN-Textual-RegressionModel-for-commodity-price-prediction
https://github.com/JoegameZhou/mPanGu-Alpha-53
https://github.com/JohannLee1996/bert
https://github.com/JohnGiorgi/compact-multi-head-self-attention-pytorch
Low Rank Factorization for Compact Multi-Head Self-Attention
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.