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 501–510 of 782 papers

TitleStatusHype
Probing Multilingual Language Models for Discourse—0
Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language InferenceCode1
BiToD: A Bilingual Multi-Domain Dataset For Task-Oriented Dialogue ModelingCode1
MergeDistill: Merging Pre-trained Language Models using Distillation—0
Language Scaling for Universal Suggested Replies Model—0
Bilingual Alignment Pre-Training for Zero-Shot Cross-Lingual TransferCode0
Syntax-augmented Multilingual BERT for Cross-lingual TransferCode1
Language Embeddings for Typology and Cross-lingual Transfer LearningCode0
How to Adapt Your Pretrained Multilingual Model to 1600 Languages—0
ZmBART: An Unsupervised Cross-lingual Transfer Framework for Language GenerationCode1
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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