{"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/precog-ltrc-iiith-at-germeval-2021-ensembling","title":"Precog-LTRC-IIITH at GermEval 2021: Ensembling Pre-Trained Language Models with Feature Engineering","arxiv_id":null,"date":"2021-09-01","proceeding":"GermEval 2021 9","authors":["T. H. Arjun","Arvindh A.","Kumaraguru Ponnurangam"],"abstract":"We describe our participation in all the subtasks of the Germeval 2021 shared task on the identification of Toxic, Engaging, and Fact-Claiming Comments. Our system is an ensemble of state-of-the-art pre-trained models finetuned with carefully engineered features. We show that feature engineering and data augmentation can be helpful when the training data is sparse. We achieve an F1 score of 66.87, 68.93, and 73.91 in Toxic, Engaging, and Fact-Claiming comment identification subtasks.","url_abs":"https://aclanthology.org/2021.germeval-1.6","url_pdf":"https://aclanthology.org/2021.germeval-1.6.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":"precog-ltrc-iiith-at-germeval-2021-ensembling","repo_url":"https://github.com/arjunth2001/GermEval-2021","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"data-augmentation","task_name":"Data Augmentation"},{"task_slug":"feature-engineering","task_name":"Feature Engineering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}