Papers by Yeonghwa Kim
UniGen: Universal Domain Generalization for Sentiment Classification via Zero-shot Dataset Generation (2024.emnlp-main)
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| Challenge: | Pre-trained language models have limited applicability for inference due to their large parameter size and limited generalization ability. |
| Approach: | They propose a method that generates a dataset regardless of the target domain . this allows for generalization of the tiny task model to any domain that shares the label space . |
| Outcome: | The proposed method achieves generalizability across domains while using a parameter set that is orders of magnitude smaller than PLMs. |