{"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/hiig-at-germeval-2022-best-of-both-worlds","title":"HIIG at GermEval 2022: Best of Both Worlds Ensemble for Automatic Text Complexity Assessment","arxiv_id":null,"date":"2022-09-01","proceeding":"GermEval 2022 9","authors":["Hadi Asghari","Freya Hewett"],"abstract":"In this paper we explain HIIG’s contribution to the shared task Text Complexity DE Challenge 2022. Our best-performing model for the task of automatically determining the complexity level of a German-language sentence is a combination of a transformer model and a classic feature-based model, which achieves a mapped root square mean error of 0.446 on the test data.","url_abs":"https://aclanthology.org/2022.germeval-1.3","url_pdf":"https://aclanthology.org/2022.germeval-1.3.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":"hiig-at-germeval-2022-best-of-both-worlds","repo_url":"https://github.com/hadiasghari/konvens22-shared-task","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}