Papers by Alina Leippert
To Clarify or not to Clarify: A Comparative Analysis of Clarification Classification with Fine-Tuning, Prompt Tuning, and Prompt Engineering (2024.naacl-srw)
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| Challenge: | Xu et al., 2019) show that pre-trained language model fine-tuning and prompt tuning are better than manual prompt engineering for clarification identification. |
| Approach: | They propose to use pre-trained language model fine-tuning, prompt tuning and manual prompt engineering to model clarification identification. |
| Outcome: | The proposed model outperforms pre-trained language model fine-tuning, prompt tuning and manual prompt engineering on the task of clarification identification. |