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 451–460 of 782 papers

TitleStatusHype
The Unreasonable Effectiveness of Model Merging for Cross-Lingual Transfer in LLMs—0
To Block or not to Block: Experiments with Machine Learning for News Comment Moderation—0
Too Late to Train, Too Early To Use? A Study on Necessity and Viability of Low-Resource Bengali LLMs—0
To Translate or Not to Translate: A Systematic Investigation of Translation-Based Cross-Lingual Transfer to Low-Resource Languages—0
Toward Cross-Lingual Definition Generation for Language Learners—0
Towards a Common Understanding of Contributing Factors for Cross-Lingual Transfer in Multilingual Language Models: A Review—0
Towards Best Practices for Training Multilingual Dense Retrieval Models—0
Towards Explainability and Fairness in Swiss Judgement Prediction: Benchmarking on a Multilingual Dataset—0
Towards Instance-Level Parser Selection for Cross-Lingual Transfer of Dependency Parsers—0
Towards Knowledge-Grounded Natural Language Understanding and Generation—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