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 491–500 of 782 papers

TitleStatusHype
UniteD-SRL: A Unified Dataset for Span- and Dependency-Based Multilingual and Cross-Lingual Semantic Role LabelingCode0
Japanese Zero Anaphora Resolution Can Benefit from Parallel Texts Through Neural Transfer Learning—0
Learning Cross-lingual Representations for Event Coreference Resolution with Multi-view Alignment and Optimal Transport—0
On the Benefit of Syntactic Supervision for Cross-lingual Transfer in Semantic Role Labeling—0
Zero-Shot Cross-Lingual Transfer is a Hard Baseline to Beat in German Fine-Grained Entity Typing—0
Limitations of Knowledge Distillation for Zero-shot Transfer Learning—0
MAD-G: Multilingual Adapter Generation for Efficient Cross-Lingual Transfer—0
Sequence Mixup for Zero-Shot Cross-Lingual Part-Of-Speech Tagging—0
Multilingual Domain Adaptation for NMT: Decoupling Language and Domain Information with Adapters—0
Cross-lingual Constituency Parsing with Linguistic Typology Knowledge—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