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 491–500 of 782 papers

TitleStatusHype
LexFit: Lexical Fine-Tuning of Pretrained Language Models—0
MulDA: A Multilingual Data Augmentation Framework for Low-Resource Cross-Lingual NER—0
Multi-View Cross-Lingual Structured Prediction with Minimum Supervision—0
GlossReader at SemEval-2021 Task 2: Reading Definitions Improves Contextualized Word Embeddings—0
PAW at SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation : Exploring Cross Lingual Transfer, Augmentations and Adversarial Training—0
Modelling Latent Translations for Cross-Lingual TransferCode1
Soft Layer Selection with Meta-Learning for Zero-Shot Cross-Lingual Transfer—0
Cross-Lingual Transfer Learning for Statistical Type Inference—0
Revisiting the Primacy of English in Zero-shot Cross-lingual Transfer—0
It's All in the Heads: Using Attention Heads as a Baseline for Cross-Lingual Transfer in Commonsense ReasoningCode1
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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