Papers with zero-shot cross-lingual transfer methods
Parameter Space Factorization for Zero-Shot Learning across Tasks and Languages (2021.tacl-1)
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| Challenge: | Currently, there are only 24 languages in the world that have not been annotated . transferring knowledge across domains is a common solution . |
| Approach: | They propose a Bayesian generative model for the space of neural parameters that factorizes into latent variables for each language and each task. |
| Outcome: | The proposed model can perform better than state-of-the-art methods with a typologically diverse sample of 33 languages from 4 continents and 11 families. |
A Simple and Effective Method to Improve Zero-Shot Cross-Lingual Transfer Learning (2022.coling-1)
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Kunbo Ding, Weijie Liu, Yuejian Fang, Weiquan Mao, Zhe Zhao, Tao Zhu, Haoyan Liu, Rong Tian, Yiren Chen
| Challenge: | Existing zero-shot cross-lingual transfer methods rely on parallel corpora or bilingual dictionaries . however, its effect is limited by the gap between embedding clusters of different languages . |
| Approach: | They propose Embedding-Push, Attention-Pull, and Robust targets to transfer English embeddings to virtual multilingual embedders without semantic loss. |
| Outcome: | Experimental results show that the proposed method outperforms existing methods on cross-lingual tasks and can achieve a better multilingual alignment. |