Frustratingly Simple Prompting-based Text Denoising
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 15 references that are in the map. First posted on arXiv 24 Feb 2024.
Builds on
6 of 15 references.
References · 6
- 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
- 2016Automatic Text Scoring Using Neural Networkscited by 51
- 2022Prompt-and-Rerank: A Method for Zero-Shot and Few-Shot Arbitrary Textual Style Transfer with Small Language Modelscited by 49
- 2023Prompt- and Trait Relation-aware Cross-prompt Essay Trait Scoringcited by 24
- 2019Contextual Text Denoising with Masked Language Modelscited by 8
- 2022Explicit Image Caption Editingcited by 7
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