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 431–440 of 782 papers

TitleStatusHype
Chinese Opinion Role Labeling with Corpus Translation: A Pivot StudyCode0
Cross-lingual Aspect-based Sentiment Analysis with Aspect Term Code-SwitchingCode1
MultiEURLEX - A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transferCode1
Zero-Shot Cross-Lingual Transfer is a Hard Baseline to Beat in German Fine-Grained Entity Typing—0
“Wikily” Supervised Neural Translation Tailored to Cross-Lingual Tasks—0
On the Benefit of Syntactic Supervision for Cross-lingual Transfer in Semantic Role Labeling—0
Frustratingly Simple but Surprisingly Strong: Using Language-Independent Features for Zero-shot Cross-lingual Semantic ParsingCode0
UniteD-SRL: A Unified Dataset for Span- and Dependency-Based Multilingual and Cross-Lingual Semantic Role LabelingCode0
MAD-G: Multilingual Adapter Generation for Efficient Cross-Lingual Transfer—0
Japanese Zero Anaphora Resolution Can Benefit from Parallel Texts Through Neural Transfer Learning—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