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 21–30 of 782 papers

TitleStatusHype
Overcoming Vocabulary Constraints with Pixel-level Fallback—0
Bridging the Linguistic Divide: A Survey on Leveraging Large Language Models for Machine Translation—0
JiraiBench: A Bilingual Benchmark for Evaluating Large Language Models' Detection of Human Self-Destructive Behavior Content in Jirai Community—0
Enhancing Small Language Models for Cross-Lingual Generalized Zero-Shot Classification with Soft Prompt Tuning—0
Untangling the Influence of Typology, Data and Model Architecture on Ranking Transfer Languages for Cross-Lingual POS Tagging—0
Language-specific Neurons Do Not Facilitate Cross-Lingual Transfer—0
Florenz: Scaling Laws for Systematic Generalization in Vision-Language Models—0
A Zero-shot Learning Method Based on Large Language Models for Multi-modal Knowledge Graph Embedding—0
Comparative Study of Zero-Shot Cross-Lingual Transfer for Bodo POS and NER Tagging Using Gemini 2.0 Flash Thinking Experimental Model—0
Char-mander Use mBackdoor! A Study of Cross-lingual Backdoor Attacks in Multilingual LLMsCode0
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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