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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 371–380 of 782 papers

TitleStatusHype
Evaluating and explaining training strategies for zero-shot cross-lingual news sentiment analysis—0
JamPatoisNLI: A Jamaican Patois Natural Language Inference Dataset—0
Japanese Zero Anaphora Resolution Can Benefit from Parallel Texts Through Neural Transfer Learning—0
JiraiBench: A Bilingual Benchmark for Evaluating Large Language Models' Detection of Human Self-Destructive Behavior Content in Jirai Community—0
Jointly Learning to Align and Summarize for Neural Cross-Lingual Summarization—0
Jointly Learning to Embed and Predict with Multiple Languages—0
JW300: A Wide-Coverage Parallel Corpus for Low-Resource Languages—0
Key ingredients for effective zero-shot cross-lingual knowledge transfer in generative tasks—0
Cross-lingual transfer learning for spoken language understanding—0
BAD-X: Bilingual Adapters Improve Zero-Shot Cross-Lingual Transfer—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