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 291–300 of 782 papers

TitleStatusHype
On the Calibration of Massively Multilingual Language ModelsCode1
A Simple and Effective Method to Improve Zero-Shot Cross-Lingual Transfer LearningCode0
Improving Low-Resource Cross-lingual Parsing with Expected Statistic RegularizationCode0
A Multi-dimensional Evaluation of Tokenizer-free Multilingual Pretrained Models—0
You Can Have Your Data and Balance It Too: Towards Balanced and Efficient Multilingual Models—0
Language Agnostic Multilingual Information Retrieval with Contrastive LearningCode0
The (In)Effectiveness of Intermediate Task Training For Domain Adaptation and Cross-Lingual Transfer Learning—0
SLICER: Sliced Fine-Tuning for Low-Resource Cross-Lingual Transfer for Named Entity RecognitionCode0
Analyzing BERT Cross-lingual Transfer Capabilities in Continual Sequence LabelingCode0
Does Meta-learning Help mBERT for Few-shot Question Generation in a Cross-lingual Transfer Setting for Indic Languages?—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