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 681–690 of 782 papers

TitleStatusHype
Language Chameleon: Transformation analysis between languages using Cross-lingual Post-training based on Pre-trained language models—0
Language Contamination Helps Explain the Cross-lingual Capabilities of English Pretrained Models—0
Language-Family Adapters for Multilingual Neural Machine Translation—0
Language-Family Adapters for Low-Resource Multilingual Neural Machine Translation—0
Language-independent Cross-lingual Contextual Representations—0
Language Scaling for Universal Suggested Replies Model—0
Language-specific Neurons Do Not Facilitate Cross-Lingual Transfer—0
Languages You Know Influence Those You Learn: Impact of Language Characteristics on Multi-Lingual Text-to-Text Transfer—0
Layer Swapping for Zero-Shot Cross-Lingual Transfer in Large Language Models—0
Learning Cross-lingual Representations for Event Coreference Resolution with Multi-view Alignment and Optimal Transport—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