https://github.com/ARBML/tkseem
Evaluating Various Tokenizers for Arabic Text Classification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Cross-lingual document classification refers to the task of using data and models available for one language for which ample such resources are available (e.g., English) to solve classification tasks in another, commonly low-resource, language.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Evaluating Various Tokenizers for Arabic Text Classification
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
MultiFiT: Efficient Multi-lingual Language Model Fine-tuning
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
BilBOWA: Fast Bilingual Distributed Representations without Word Alignments
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
Multilingual Distributed Representations without Word Alignment
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
Learning Crosslingual Word Embeddings without Bilingual Corpora
MultiFiT: Efficient Multi-lingual Language Model Fine-tuning
AraCOVID19-MFH: Arabic COVID-19 Multi-label Fake News and Hate Speech Detection Dataset
A Corpus for Multilingual Document Classification in Eight Languages
Exploring Tokenization Strategies and Vocabulary Sizes for Enhanced Arabic Language Models
MultiFiT: Efficient Multi-lingual Language Model Fine-tuning
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.