Papers with few-sample transfer learning scenarios
S4-Tuning: A Simple Cross-lingual Sub-network Tuning Method (2022.acl-short)
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| Challenge: | Existing multilingual pre-trained language models allow to adapt to target languages with only few labeled examples. |
| Approach: | They propose a simple cross-lingual sub-network tuning method that detects the most essential sub-netzwork for each target language and updates it during fine-tuning. |
| Outcome: | The proposed method improves on three multi-lingual tasks involving 37 different languages. |