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 441–450 of 782 papers

TitleStatusHype
Text Generation Models for Luxembourgish with Limited Data: A Balanced Multilingual Strategy—0
Text-to-Speech for Under-Resourced Languages: Phoneme Mapping and Source Language Selection in Transfer Learning—0
The Best of both Worlds: Dual Channel Language modeling for Hope Speech Detection in low-resourced Kannada—0
The CMU-LTI submission to the SIGMORPHON 2020 Shared Task 0: Language-Specific Cross-Lingual Transfer—0
The Effects of Input Type and Pronunciation Dictionary Usage in Transfer Learning for Low-Resource Text-to-Speech—0
The First Multilingual Model For The Detection of Suicide Texts—0
The Model Arena for Cross-lingual Sentiment Analysis: A Comparative Study in the Era of Large Language Models—0
The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm—0
The Reality of Multi-Lingual Machine Translation—0
The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection—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