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 171–180 of 782 papers

TitleStatusHype
A Unified System for Aggression Identification in English Code-Mixed and Uni-Lingual Texts—0
Building Dialogue Understanding Models for Low-resource Language Indonesian from Scratch—0
DA-Net: A Disentangled and Adaptive Network for Multi-Source Cross-Lingual Transfer Learning—0
Data-adaptive Transfer Learning for Translation: A Case Study in Haitian and Jamaican—0
Building a Japanese Document-Level Relation Extraction Dataset Assisted by Cross-Lingual Transfer—0
BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer—0
Anchor-based Bilingual Word Embeddings for Low-Resource Languages—0
Acoustics Based Intent Recognition Using Discovered Phonetic Units for Low Resource Languages—0
Cross-lingual Approaches for Task-specific Dialogue Act Recognition—0
Cross-lingual Transfer Learning for COVID-19 Outbreak Alignment—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