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 451–460 of 782 papers

TitleStatusHype
A Survey of Multilingual Models for Automatic Speech Recognition—0
Oolong: Investigating What Makes Transfer Learning Hard with Controlled StudiesCode0
Enhancing Cross-lingual Prompting with Dual Prompt AugmentationCode0
Surprisingly Simple Adapter Ensembling for Zero-Shot Cross-Lingual Sequence Tagging—0
XQA-DST: Multi-Domain and Multi-Lingual Dialogue State Tracking—0
BAD-X: Bilingual Adapters Improve Zero-Shot Cross-Lingual Transfer—0
Frustratingly Simple Regularization to Improve Zero-shot Cross-lingual Robustness—0
An Empirical Study on Cross-Lingual and Cross-Domain Transfer for Legal Judgment Prediction—0
Realistic Zero-Shot Cross-Lingual Transfer in Legal Topic Classification—0
When More is not Necessary Better: Multilingual Auxiliary Tasks for Zero-Shot Cross-Lingual Transfer of Hate Speech Detection Models—0
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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