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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 61–70 of 782 papers

TitleStatusHype
Cross-lingual Back-Parsing: Utterance Synthesis from Meaning Representation for Zero-Resource Semantic ParsingCode0
Evaluating and explaining training strategies for zero-shot cross-lingual news sentiment analysis—0
EMMA-500: Enhancing Massively Multilingual Adaptation of Large Language ModelsCode0
Cross-lingual transfer of multilingual models on low resource African LanguagesCode0
Exploring the Impact of Data Quantity on ASR in Extremely Low-resource Languages—0
SpeechTaxi: On Multilingual Semantic Speech Classification—0
A multilingual training strategy for low resource Text to Speech—0
Exploring Multiple Strategies to Improve Multilingual Coreference Resolution in CorefUDCode0
Defining Boundaries: The Impact of Domain Specification on Cross-Language and Cross-Domain Transfer in Machine Translation—0
RedWhale: An Adapted Korean LLM Through Efficient Continual Pretraining—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