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 421–430 of 782 papers

TitleStatusHype
Analyzing the Mono- and Cross-Lingual Pretraining Dynamics of Multilingual Language Models—0
Local Byte Fusion for Neural Machine TranslationCode0
Multi2WOZ: A Robust Multilingual Dataset and Conversational Pretraining for Task-Oriented DialogCode0
Phylogeny-Inspired Adaptation of Multilingual Models to New LanguagesCode0
Persian Natural Language Inference: A Meta-learning approachCode0
Feature Aggregation in Zero-Shot Cross-Lingual Transfer Using Multilingual BERT—0
OneAligner: Zero-shot Cross-lingual Transfer with One Rich-Resource Language Pair for Low-Resource Sentence Retrieval—0
A Balanced Data Approach for Evaluating Cross-Lingual Transfer: Mapping the Linguistic Blood BankCode0
GL-CLeF: A Global–Local Contrastive Learning Framework for Cross-lingual Spoken Language UnderstandingCode0
Cloze Evaluation for Deeper Understanding of Commonsense Stories in IndonesianCode0
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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