Frustratingly Simple Prompting-based Text Denoising
Fuente:
arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866917597348364288 |
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| author | Park, Jungyeul Qiu, Mengyang |
| author_facet | Park, Jungyeul Qiu, Mengyang |
| contents | This paper introduces a novel perspective on the automated essay scoring (AES) task, challenging the conventional view of the ASAP dataset as a static entity. Employing simple text denoising techniques using prompting, we explore the dynamic potential within the dataset. While acknowledging the previous emphasis on building regression systems, our paper underscores how making minor changes to a dataset through text denoising can enhance the final results. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_15931 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Frustratingly Simple Prompting-based Text Denoising Park, Jungyeul Qiu, Mengyang Computation and Language This paper introduces a novel perspective on the automated essay scoring (AES) task, challenging the conventional view of the ASAP dataset as a static entity. Employing simple text denoising techniques using prompting, we explore the dynamic potential within the dataset. While acknowledging the previous emphasis on building regression systems, our paper underscores how making minor changes to a dataset through text denoising can enhance the final results. |
| title | Frustratingly Simple Prompting-based Text Denoising |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2402.15931 |