https://github.com/ikergarcia1996/Iker-Garcia-Ferrero
A Common Semantic Space for Monolingual and Cross-Lingual Meta-Embeddings
Papers with Code 아카이브
Cross-Lingual
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Cross-lingual natural language processing is the task of using data and models available for one language for which ample such resources are available (e.g., English) to solve tasks in another, commonly more low-resource, language.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ilhamfp/indonesian-text-classification-multilingual
https://github.com/imamathcat/LASER_Dependencies
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
https://github.com/inzva/turkish-glove
https://github.com/jeongukjae/smaller-labse
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
https://github.com/jiamingkong/infoxlm_paddle
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
https://github.com/karanwxliaa/cross-lingual-transfer-of-multilingual-models-on-low-resource-african-languages
Cross-lingual transfer of multilingual models on low resource African Languages
https://github.com/karlmoritz/bicvm
Multilingual Distributed Representations without Word Alignment
https://github.com/kheeong/XLM_OWN
https://github.com/kingoflolz/mesh-transformer-jax
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
https://github.com/kmkwon94/ainize-laser
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
https://github.com/labmlai/annotated_deep_learning_paper_implementations
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
https://github.com/lancelee82/necklace
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
https://github.com/langtech-bsc/langtech_tokenizers
Efficient Language Model Training through Cross-Lingual and Progressive Transfer Learning
https://github.com/liatb282/metaxlr
MetaXL: Meta Representation Transformation for Low-resource Cross-lingual Learning
https://github.com/lizhou21/cultural-compass
https://github.com/longdt219/xlingualemb
Learning Crosslingual Word Embeddings without Bilingual Corpora
https://github.com/lsqdecodebox/NLP-Comptition-review
https://github.com/lukexyz/Language-Models
MultiFiT: Efficient Multi-lingual Language Model Fine-tuning
https://github.com/manshri/tesum
mT5: A massively multilingual pre-trained text-to-text transformer
https://github.com/maroxtn/tun-sentiment
AraCOVID19-MFH: Arabic COVID-19 Multi-label Fake News and Hate Speech Detection Dataset
https://github.com/martincjespersen/DaAnonymization
https://github.com/microsoft/unilm/tree/master/infoxlm
InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training
https://github.com/msr-lit/multilingualbias
Gender Bias in Multilingual Embeddings and Cross-Lingual Transfer
https://github.com/n-waves/multifit
A Corpus for Multilingual Document Classification in Eight Languages
https://github.com/neulab/pivot-based-entity-linking
https://github.com/nlp-uoregon/trankit
https://github.com/nourmorsy/PremioLLM
Exploring Tokenization Strategies and Vocabulary Sizes for Enhanced Arabic Language Models
https://github.com/nthakur20/income
Unsupervised Dense Information Retrieval with Contrastive Learning
https://github.com/opennlg/openba-v2
Universal NER: A Gold-Standard Multilingual Named Entity Recognition Benchmark
https://github.com/pasinit/xlwic-runs
XL-WiC: A Multilingual Benchmark for Evaluating Semantic Contextualization
https://github.com/piegu/language-models
MultiFiT: Efficient Multi-lingual Language Model Fine-tuning
https://github.com/prabhakar267/LASER-improved
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
https://github.com/pwc-1/Paper-5/tree/main/mluke
mLUKE: The Power of Entity Representations in Multilingual Pretrained Language Models
https://github.com/pwc-1/Paper-5/tree/main/mt5
mT5: A massively multilingual pre-trained text-to-text transformer
https://github.com/pwc-1/Paper-9/tree/main/1/xlm_roberta
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.