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 81–90 of 782 papers

TitleStatusHype
Cross-Lingual Transfer Learning for Speech Translation—0
Too Late to Train, Too Early To Use? A Study on Necessity and Viability of Low-Resource Bengali LLMs—0
Self-Translate-Train: Enhancing Cross-Lingual Transfer of Large Language Models via Inherent Capability—0
Breaking the Script Barrier in Multilingual Pre-Trained Language Models with Transliteration-Based Post-Training AlignmentCode0
T-FREE: Subword Tokenizer-Free Generative LLMs via Sparse Representations for Memory-Efficient EmbeddingsCode2
The Model Arena for Cross-lingual Sentiment Analysis: A Comparative Study in the Era of Large Language Models—0
SSP: Self-Supervised Prompting for Cross-Lingual Transfer to Low-Resource Languages using Large Language ModelsCode0
The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm—0
A Three-Pronged Approach to Cross-Lingual Adaptation with Multilingual LLMs—0
Large Language Models Are Cross-Lingual Knowledge-Free ReasonersCode0
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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