Soft Language Prompts for Language Transfer
- URL: http://arxiv.org/abs/2407.02317v1
- Date: Tue, 2 Jul 2024 14:50:03 GMT
- Title: Soft Language Prompts for Language Transfer
- Authors: Ivan Vykopal, Simon Ostermann, Marián Šimko,
- Abstract summary: Cross-lingual knowledge transfer, especially between high- and low-resource languages, remains a challenge in natural language processing (NLP)
This study offers insights for improving cross-lingual NLP applications through the combination of parameter-efficient fine-tuning methods.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Cross-lingual knowledge transfer, especially between high- and low-resource languages, remains a challenge in natural language processing (NLP). This study offers insights for improving cross-lingual NLP applications through the combination of parameter-efficient fine-tuning methods. We systematically explore strategies for enhancing this cross-lingual transfer through the incorporation of language-specific and task-specific adapters and soft prompts. We present a detailed investigation of various combinations of these methods, exploring their efficiency across six languages, focusing on three low-resource languages, including the to our knowledge first use of soft language prompts. Our findings demonstrate that in contrast to claims of previous work, a combination of language and task adapters does not always work best; instead, combining a soft language prompt with a task adapter outperforms other configurations in many cases.
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