{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/the-re-label-method-for-data-centric-machine","title":"The Re-Label Method For Data-Centric Machine Learning","arxiv_id":"2302.04391","date":"2023-02-09","proceeding":null,"authors":["Tong Guo"],"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 dev dataset evaluation results and human evaluation results verify our idea.","url_abs":"https://arxiv.org/abs/2302.04391v9","url_pdf":"https://arxiv.org/pdf/2302.04391v9.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"the-re-label-method-for-data-centric-machine","repo_url":"https://github.com/guotong1988/Automatic-Label-Error-Correction","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"click-through-rate-prediction","task_name":"Click-Through Rate Prediction"},{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"label-error-detection","task_name":"Label Error Detection"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"text-classification","task_name":"Text Classification"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/label-error-detection-on-trec-6","task":"Label Error Detection","dataset":"TREC-6","model":"github.com/guotong1988/Automatic-Label-Error-Correction","rank_in_archive_order":1,"of":1,"metrics":{"Accuracy":"99.0"},"uses_additional_data":false},{"leaderboard":"/sota/text-classification-on-trec-6","task":"Text Classification","dataset":"TREC-6","model":"Automatic Label Error Correction","rank_in_archive_order":1,"of":19,"metrics":{"Error":"0.40"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}