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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 211–220 of 782 papers

TitleStatusHype
Distilling Efficient Language-Specific Models for Cross-Lingual TransferCode0
The Effects of Input Type and Pronunciation Dictionary Usage in Transfer Learning for Low-Resource Text-to-Speech—0
Improved Cross-Lingual Transfer Learning For Automatic Speech Translation—0
SLABERT Talk Pretty One Day: Modeling Second Language Acquisition with BERT—0
Pre-Trained Language-Meaning Models for Multilingual Parsing and GenerationCode0
Why Does Zero-Shot Cross-Lingual Generation Fail? An Explanation and a Solution—0
Free Lunch: Robust Cross-Lingual Transfer via Model Checkpoint AveragingCode0
Towards a Common Understanding of Contributing Factors for Cross-Lingual Transfer in Multilingual Language Models: A Review—0
Revisiting non-English Text Simplification: A Unified Multilingual BenchmarkCode1
Meta-learning For Vision-and-language Cross-lingual Transfer—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