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 611–620 of 782 papers

TitleStatusHype
End-to-end Text-to-speech for Low-resource Languages by Cross-Lingual Transfer Learning—0
English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too—0
English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too—0
Enhancing Cross-lingual Prompting with Two-level Augmentation—0
Enhancing Cross-task Transfer of Large Language Models via Activation Steering—0
Enhancing LLM Language Adaption through Cross-lingual In-Context Pre-training—0
Enhancing Small Language Models for Cross-Lingual Generalized Zero-Shot Classification with Soft Prompt Tuning—0
EntityCS: Improving Zero-Shot Cross-lingual Transfer with Entity-Centric Code Switching—0
Errator: a Tool to Help Detect Annotation Errors in the Universal Dependencies Project—0
Evaluating and explaining training strategies for zero-shot cross-lingual news sentiment analysis—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