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 476–500 of 782 papers

TitleStatusHype
An Empirical Study on Cross-Lingual and Cross-Domain Transfer for Legal Judgment Prediction—0
Any-language frame-semantic parsing—0
Are All Languages Created Equal in Multilingual BERT?—0
A Semi-universal Pipelined Approach to the CoNLL 2017 UD Shared Task—0
Assessing the Syntactic Capabilities of Transformer-based Multilingual Language Models—0
A Study of Cross-Lingual Ability and Language-specific Information in Multilingual BERT—0
A Survey Of Cross-lingual Word Embedding Models—0
A Survey of Multilingual Models for Automatic Speech Recognition—0
A Systematic Analysis of Subwords and Cross-Lingual Transfer in Multilingual Translation—0
A Three-Pronged Approach to Cross-Lingual Adaptation with Multilingual LLMs—0
Automatic Interlinear Glossing for Under-Resourced Languages Leveraging Translations—0
Auxiliary Subword Segmentations as Related Languages for Low Resource Multilingual Translation—0
A Zero-shot Learning Method Based on Large Language Models for Multi-modal Knowledge Graph Embedding—0
BAD-X: Bilingual Adapters Improve Zero-Shot Cross-Lingual Transfer—0
Bailong: Bilingual Transfer Learning based on QLoRA and Zip-tie Embedding—0
Bilingual Adaptation of Monolingual Foundation Models—0
Bilingual Language Modeling, A transfer learning technique for Roman Urdu—0
Bitext Mining Using Distilled Sentence Representations for Low-Resource Languages—0
Blessing of Multilinguality: A Systematic Analysis of Multilingual In-Context Learning—0
Cross-lingual QA: A Key to Unlocking In-context Cross-lingual Performance—0
Bridging the Language Gap: Enhancing Multilingual Prompt-Based Code Generation in LLMs via Zero-Shot Cross-Lingual Transfer—0
Bridging the Language Gap: Knowledge Injected Multilingual Question Answering—0
Bridging the Linguistic Divide: A Survey on Leveraging Large Language Models for Machine Translation—0
BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer—0
Building a Japanese Document-Level Relation Extraction Dataset Assisted by 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