https://github.com/google-research-datasets/wiki-reading
WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia
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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>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Multiview Learning of Weighted Majority Vote by Bregman Divergence Minimization
XLNet: Generalized Autoregressive Pretraining for Language Understanding
What you can cram into a single vector: Probing sentence embeddings for linguistic properties
Real-time Convolutional Neural Networks for Emotion and Gender Classification
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Universal Language Model Fine-tuning for Text Classification
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
GPT-Sentinel: Distinguishing Human and ChatGPT Generated Content
SCDV : Sparse Composite Document Vectors using soft clustering over distributional representations
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.