Zero Shot Cross Lingual Transfer

Zero-Shot Cross-Lingual Transfer is a technique in the field of natural language processing aimed at enabling pre-trained models to perform task inference directly on unseen target languages without the need for additional annotated data in the target language. This technology enhances the model's generalization capability in multilingual environments, achieving efficient language understanding and generation, and has significant application value, especially in the processing of resource-scarce languages.