Papers by Jeongwoo Kang
Should Cross-Lingual AMR Parsing go Meta? An Empirical Assessment of Meta-Learning and Joint Learning AMR Parsing (2024.findings-emnlp)
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| Challenge: | Cross-lingual AMR parsing is a task of predicting AMR graphs in a target language when training data is available only in . et al. (2018) evaluated meta-learning for cross-lingual parse in Croatian, Farsi, Korean, Chinese, and French. |
| Approach: | They propose to use meta-learning to tackle cross-lingual AMR parsing in a target language . they evaluate their models in k-shot scenarios and compare them to classical joint learning . |
| Outcome: | The proposed model performs better in 0-shot evaluation for Croatian, Farsi, Korean, Chinese, and French. |