https://github.com/YF-W/Tri-GFN
공식 코드Tri-Learn Graph Fusion Network for Attributed Graph Clustering
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/YuweiYin/CROP
공식 코드https://github.com/aaronmueller/contextualized-topic-models
공식 코드Fine-tuning Encoders for Improved Monolingual and Zero-shot Polylingual Neural Topic Modeling
https://github.com/abteen/americasnli
공식 코드https://github.com/adapter-hub/unks_everywhere
공식 코드UNKs Everywhere: Adapting Multilingual Language Models to New Scripts
https://github.com/adapter-hub/xgqa
공식 코드https://github.com/afshinrahimi/mmner
공식 코드https://github.com/aggiejiang/crosslingual-offensive-language-survey
공식 코드https://github.com/aggiejiang/sexwes
공식 코드https://github.com/ai-forever/mgpt
공식 코드https://github.com/alanansell/bistil
공식 코드Distilling Efficient Language-Specific Models for Cross-Lingual Transfer
https://github.com/alankarj/cross_lingual_ner
공식 코드Entity Projection via Machine Translation for Cross-Lingual NER
https://github.com/alecokas/swahili-text-gcn
공식 코드https://github.com/aleph-alpha/trigrams
공식 코드https://github.com/alexeyev/kyrgyz-multi-label-topic-classification
공식 코드Benchmarking Multilabel Topic Classification in the Kyrgyz Language
https://github.com/altsoph/EENLP
공식 코드https://github.com/amazon-research/multiatis
공식 코드End-to-End Slot Alignment and Recognition for Cross-Lingual NLU
https://github.com/anaryegen/few_shot_argument_mining
공식 코드Argument Mining in Data Scarce Settings: Cross-lingual Transfer and Few-shot Techniques
https://github.com/andreawwenyi/hyperpolyglot
공식 코드Hyperpolyglot LLMs: Cross-Lingual Interpretability in Token Embeddings
https://github.com/andreeaiana/nase
공식 코드https://github.com/andreeaiana/xmind
공식 코드MIND Your Language: A Multilingual Dataset for Cross-lingual News Recommendation
https://github.com/antonisa/inflection
공식 코드https://github.com/aremuadeolajr/naijarc
공식 코드NaijaRC: A Multi-choice Reading Comprehension Dataset for Nigerian Languages
https://github.com/arijrb/multilingual-auxiliary-tasks-training-bridging-the-gap-between-languages-for-zero-shot-transfer-of-
공식 코드https://github.com/artetxem/esxnli
공식 코드https://github.com/arusl/anlp_nlp2022_a6-1
공식 코드https://github.com/asofiaoliveira/srl_bert_pt
공식 코드Improving Portuguese Semantic Role Labeling with Transformers and Transfer Learning
https://github.com/bebing93/devil-in-details
공식 코드https://github.com/befittingcrown/ekohate
공식 코드https://github.com/benjamin-mlr/first-align-then-predict
공식 코드First Align, then Predict: Understanding the Cross-Lingual Ability of Multilingual BERT
https://github.com/berniebear/Multi-HT100M
공식 코드Multilingual Multimodal Pre-training for Zero-Shot Cross-Lingual Transfer of Vision-Language Models
https://github.com/bigscience-workshop/xmtf
공식 코드https://github.com/billywzh717/n24news
공식 코드https://github.com/bkhmsi/cultural-trends
공식 코드https://github.com/bkolosk1/kbnr
공식 코드Knowledge Graph informed Fake News Classification via Heterogeneous Representation Ensembles
https://github.com/blazejdolicki/multilingual-analysis
공식 코드Analysing The Impact Of Linguistic Features On Cross-Lingual Transfer
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.