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 431–440 of 782 papers

TitleStatusHype
Word-Level Representation From Bytes For Language Modeling—0
xGQA: Cross-Lingual Visual Question Answering—0
XLA: A Robust Unsupervised Data Augmentation Framework for Cross-Lingual NLP—0
XQA-DST: Multi-Domain and Multi-Lingual Dialogue State Tracking—0
X-SNS: Cross-Lingual Transfer Prediction through Sub-Network Similarity—0
You Can Have Your Data and Balance It Too: Towards Balanced and Efficient Multilingual Models—0
Zero-resource Dependency Parsing: Boosting Delexicalized Cross-lingual Transfer with Linguistic Knowledge—0
Zero-Resource Multilingual Model Transfer: Learning What to Share—0
Zero-shot Cross-Language Transfer of Monolingual Entity Linking Models—0
Zero-Shot Cross-lingual Classification Using Multilingual Neural Machine Translation—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