preprint
Open access
Re-Label Is All You Need
Research footprint
At a glance
- Citations
- 0
- References
- 6
- Comments
- 0
Paper overview
Abstract
In industry deep learning application, our manually labeled data has a certain number of noisy data. To solve this problem and achieve more than 90 score in dev dataset, we present a simple method to find the noisy data and re-label the noisy data by human, given the model predictions as references in human labeling. In this paper, we illustrate our idea for a broad set of deep learning tasks, includes classification, sequence tagging, object detection, sequence generation, click-through rate prediction. The experimental results and human evaluation results verify our idea.
Record transparency
Publication details
- DOI
- 10.36227/techrxiv.17128475.v3
- OpenAlex
- W4287837502
- Document type
- preprint
- Language
- EN
- Last metadata update
Comments
Log in to join the discussion.