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 301–310 of 782 papers

TitleStatusHype
Exploring Pretraining via Active Forgetting for Improving Cross Lingual Transfer for Decoder Language Models—0
Cross-Lingual Optimization for Language Transfer in Large Language Models—0
Cross-lingual intent classification in a low resource industrial setting—0
Cross-Lingual Parser Selection for Low-Resource Languages—0
Cross-Lingual Part-of-Speech Tagging through Ambiguous Learning—0
Florenz: Scaling Laws for Systematic Generalization in Vision-Language Models—0
Fortification of Neural Morphological Segmentation Models for Polysynthetic Minimal-Resource Languages—0
FrameNet on the Way to Babel: Creating a Bilingual FrameNet Using Wiktionary as Interlingual Connection—0
Cross-Lingual Relation Extraction with Transformers—0
How to Translate Your Samples and Choose Your Shots? Analyzing Translate-train & Few-shot 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