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 721–730 of 782 papers

TitleStatusHype
Mini-Model Adaptation: Efficiently Extending Pretrained Models to New Languages via Aligned Shallow Training—0
Mitigating the Linguistic Gap with Phonemic Representations for Robust Cross-lingual Transfer—0
Model-Agnostic Meta-Learning for Multilingual Hate Speech Detection—0
Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing—0
Model Selection for Cross-Lingual Transfer using a Learned Scoring Function—0
MulDA: A Multilingual Data Augmentation Framework for Low-Resource Cross-Lingual NER—0
Multi2WOZ: A Robust Multilingual Dataset and Conversational Pretraining for Task-Oriented Dialog—0
Multi-Agent Collaboration for Multilingual Code Instruction Tuning—0
Multi-Level Contrastive Learning for Cross-Lingual Alignment—0
Multilingual and Zero-Shot is Closing in on Monolingual Web Register Classification—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