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 41–50 of 782 papers

TitleStatusHype
On the Applicability of Zero-Shot Cross-Lingual Transfer Learning for Sentiment Classification in Distant Language PairsCode0
The First Multilingual Model For The Detection of Suicide Texts—0
Cross-Lingual Transfer of Debiasing and Detoxification in Multilingual LLMs: An Extensive InvestigationCode0
Cross-Dialect Information Retrieval: Information Access in Low-Resource and High-Variance LanguagesCode0
Beyond Data Quantity: Key Factors Driving Performance in Multilingual Language ModelsCode0
Bridging the Gap: Enhancing LLM Performance for Low-Resource African Languages with New Benchmarks, Fine-Tuning, and Cultural AdjustmentsCode1
Text Generation Models for Luxembourgish with Limited Data: A Balanced Multilingual Strategy—0
Multilingual Large Language Models: A Systematic SurveyCode1
Zero-shot Cross-lingual Transfer Learning with Multiple Source and Target Languages for Information Extraction: Language Selection and Adversarial Training—0
When Does Classical Chinese Help? Quantifying Cross-Lingual Transfer in Hanja and KanbunCode0
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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