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 411–420 of 782 papers

TitleStatusHype
Self-Distillation for Model Stacking Unlocks Cross-Lingual NLU in 200+ Languages—0
Self-Supervised Representations Improve End-to-End Speech Translation—0
Self-Translate-Train: Enhancing Cross-Lingual Transfer of Large Language Models via Inherent Capability—0
Semantic Pivots Enable Cross-Lingual Transfer in Large Language Models—0
SenWiCh: Sense-Annotation of Low-Resource Languages for WiC using Hybrid Methods—0
Sequence Mixup for Zero-Shot Cross-Lingual Part-Of-Speech Tagging—0
Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning—0
Sharing, Teaching and Aligning: Knowledgeable Transfer Learning for Cross-Lingual Machine Reading Comprehension—0
SIGTYP 2020 Shared Task: Prediction of Typological Features—0
SLABERT Talk Pretty One Day: Modeling Second Language Acquisition with BERT—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