SOTAVerified

Cross-Lingual Transfer

Cross-lingual transfer refers to transfer learning 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.

Papers

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Showing 351–360 of 782 papers

TitleStatusHype
Phylogeny-Inspired Adaptation of Multilingual Models to New LanguagesCode0
Persian Natural Language Inference: A Meta-learning approachCode0
OneAligner: Zero-shot Cross-lingual Transfer with One Rich-Resource Language Pair for Low-Resource Sentence Retrieval—0
Feature Aggregation in Zero-Shot Cross-Lingual Transfer Using Multilingual BERT—0
A Balanced Data Approach for Evaluating Cross-Lingual Transfer: Mapping the Linguistic Blood BankCode0
Enhancing Cross-lingual Transfer by Manifold MixupCode1
Machine Translation for Livonian: Catering to 20 Speakers—0
GL-CLeF: A Global–Local Contrastive Learning Framework for Cross-lingual Spoken Language UnderstandingCode0
Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 LanguagesCode1
Towards Making the Most of Cross-Lingual Transfer for Zero-Shot Neural Machine TranslationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PaLM 2 (few-shot)Accuracy94.4—Unverified
2mT0-13BAccuracy84.45—Unverified
3RoBERTa Large (translate test)Accuracy76.05—Unverified
4BLOOMZAccuracy75.5—Unverified
5MAD-X BaseAccuracy60.94—Unverified
6mGPTAccuracy55.5—Unverified