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 271–280 of 782 papers

TitleStatusHype
Efficiently Adapting Pretrained Language Models To New Languages—0
Vicinal Risk Minimization for Few-Shot Cross-lingual Transfer in Abusive Language Detection—0
X-SNS: Cross-Lingual Transfer Prediction through Sub-Network Similarity—0
Learning Transfers over Several Programming Languages—0
A Multi-Modal Multilingual Benchmark for Document Image Classification—0
ZGUL: Zero-shot Generalization to Unseen Languages using Multi-source Ensembling of Language AdaptersCode0
Improving Cross-Lingual Transfer through Subtree-Aware Word ReorderingCode0
Investigating Bias in Multilingual Language Models: Cross-Lingual Transfer of Debiasing TechniquesCode0
One For All & All For One: Bypassing Hyperparameter Tuning with Model Averaging For Cross-Lingual TransferCode0
To token or not to token: A Comparative Study of Text Representations for Cross-Lingual TransferCode0
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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