Identifying the Correlation Between Language Distance and Cross-Lingual Transfer in a Multilingual Representation Space
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866909151556272128 |
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| author | Philippy, Fred Guo, Siwen Haddadan, Shohreh |
| author_facet | Philippy, Fred Guo, Siwen Haddadan, Shohreh |
| contents | Prior research has investigated the impact of various linguistic features on cross-lingual transfer performance. In this study, we investigate the manner in which this effect can be mapped onto the representation space. While past studies have focused on the impact on cross-lingual alignment in multilingual language models during fine-tuning, this study examines the absolute evolution of the respective language representation spaces produced by MLLMs. We place a specific emphasis on the role of linguistic characteristics and investigate their inter-correlation with the impact on representation spaces and cross-lingual transfer performance. Additionally, this paper provides preliminary evidence of how these findings can be leveraged to enhance transfer to linguistically distant languages. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2305_02151 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Identifying the Correlation Between Language Distance and Cross-Lingual Transfer in a Multilingual Representation Space Philippy, Fred Guo, Siwen Haddadan, Shohreh Computation and Language Artificial Intelligence Machine Learning Prior research has investigated the impact of various linguistic features on cross-lingual transfer performance. In this study, we investigate the manner in which this effect can be mapped onto the representation space. While past studies have focused on the impact on cross-lingual alignment in multilingual language models during fine-tuning, this study examines the absolute evolution of the respective language representation spaces produced by MLLMs. We place a specific emphasis on the role of linguistic characteristics and investigate their inter-correlation with the impact on representation spaces and cross-lingual transfer performance. Additionally, this paper provides preliminary evidence of how these findings can be leveraged to enhance transfer to linguistically distant languages. |
| title | Identifying the Correlation Between Language Distance and Cross-Lingual Transfer in a Multilingual Representation Space |
| topic | Computation and Language Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2305.02151 |