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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/pipidog/QNLP
https://github.com/pisalore/roberta_results
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/piyush2896/CNN-Text-Classifier
https://github.com/plkmo/BERT-Relation-Extraction
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
https://github.com/plkmo/Bible_Text_GCN
https://github.com/plkumjorn/FIND
https://github.com/plusross/grcn
https://github.com/polkadottedwalrus/Fanfiction
https://github.com/polzinben/TensorFlow_NLP
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/pommedeterresautee/fastrtext
https://github.com/ppapalampidi/GraphTP
https://github.com/ppapalampidi/SUMMER
https://github.com/ppke-nlpg/fastText_factored-cbow
https://github.com/prabhakar267/LASER-improved
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
https://github.com/prajjwal1/language-modelling
Universal Language Model Fine-tuning for Text Classification
https://github.com/prakashpandey9/Text-Classification-Pytorch
https://github.com/pranawmishra/SkimLit
PubMed 200k RCT: a Dataset for Sequential Sentence Classification in Medical Abstracts
https://github.com/pranjalg96/Stylized-Image-captioning
https://github.com/printfer/CS6490_NetworkSecurity_FinalProject
https://github.com/prithviraj-maurya/alexa-point-of-view-dataset
Converting the Point of View of Messages Spoken to Virtual Assistants
https://github.com/protonx-tf-03-projects/CharCNN
Character-level Convolutional Networks for Text Classification
https://github.com/prrao87/fine-grained-sentiment
https://github.com/ps2811/Bert-Multi-Label-Text-Classification-GitVersion
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/pwc-1/Paper-10/tree/main/squeezebert
SqueezeBERT: What can computer vision teach NLP about efficient neural networks?
https://github.com/pwc-1/Paper-8/tree/main/big_bird
https://github.com/pwc-1/Paper-8/tree/main/bigbird_pegasus
https://github.com/pwc-1/Paper-9/tree/main/1/xlnet
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/pwc-1/Paper-9/tree/main/2/mt5
MT6: Multilingual Pretrained Text-to-Text Transformer with Translation Pairs
https://github.com/pwc-1/Paper-9/tree/main/5/xlm_roberta
https://github.com/pwc-1/Paper-9/tree/main/5/xlnet
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/pytorch/captum
Towards better understanding of gradient-based attribution methods for Deep Neural Networks
https://github.com/pytorch/pytorch/blob/main/torch/nn/functional.py
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
https://github.com/pytorch/text
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/qampspring2023/qgpt-issue-31
Quantum Self-Attention Neural Networks for Text Classification
https://github.com/qbxlvnf11/BERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.