--- title: "Georg Groh — author profile and papers — Elamur Research" description: "Georg Groh, Technical University of Munich: 2 papers on Elamur Research (2020–2023), h-index 22 — affiliations, topics, co-authors and…" canonical: "https://research.elamur.ai/free/en/authors/georg-groh/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/georg-groh/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Georg Groh # Georg Groh Georg Groh has 2 papers in our library, in 2020–2023, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Daryna Dementieva](https://md.research.elamur.ai/free/en/authors/daryna-dementieva/). 2 papers in our library · 2020–2023 [OpenAlex](https://openalex.org/A5004398345) · [ORCID](https://orcid.org/0000-0002-5942-2297) · [Wikidata](https://www.wikidata.org/wiki/Q91538954) · [**h-index 22**](https://openalex.org/authors/A5004398345) · [175 works](https://openalex.org/works?filter=author.id:A5004398345) · [8,827 citations](https://openalex.org/works?filter=author.id:A5004398345&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/georg-groh/#papers) · [🔗 Cited 308 times in our library](https://md.research.elamur.ai/free/en/authors/georg-groh/cited-by/) · [4 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #346](https://md.research.elamur.ai/free/en/paper-stars/page/4/#star-346) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Georg+Groh) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Georg+Groh) · [dblp](https://dblp.org/search?q=Georg+Groh) · [ACL Anthology](https://aclanthology.org/search/?q=Georg+Groh) ## Affiliations [🎓**Technical University of Munich** Munich · Germany 2002–2026 · 140 papers*current*](https://md.research.elamur.ai/free/en/universities/technical-university-of-munich/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. ## Concepts, shelves and topics Of its works in our library: the number of works on each and its rating among them. 📚 Shelves 8 The field of science this work belongs to (OpenAlex fields).[Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Medicine · 1 work](https://md.research.elamur.ai/free/en/shelves/medicine/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Education · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/education/) · [Health Informatics · 1 work](https://md.research.elamur.ai/free/en/shelves/medicine/health-informatics/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Safety Research · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/safety-research/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/) 🧭 Topics 1 Research subjects and languages the work is about.[Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) 💡 Concepts 1 Key ideas and methods explained on our concept pages.[Language model · 1 work](https://md.research.elamur.ai/free/en/concepts/language-model/) ## Works by year ### 2020s [**2023** 1 paper ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education](https://md.research.elamur.ai/free/en/papers/kasneci-2023-chatgpt-good-opportunities-challenges-large/) · [**2020** 1 paper Identifying and Measuring Annotator Bias Based on Annotators' Demographic Characteristics](https://md.research.elamur.ai/free/en/papers/kuwatly-2020-identifying-measuring-annotator-bias-based/) ## Papers The most cited first (OpenAlex and our library). 1. **[ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education](https://md.research.elamur.ai/free/en/papers/kasneci-2023-chatgpt-good-opportunities-challenges-large/)** *(2023 · 7,436 citations)* This position paper asks how large language models such as GPT-3 and ChatGPT could change education and what risks come with them. 2. **[Identifying and Measuring Annotator Bias Based on Annotators' Demographic Characteristics](https://md.research.elamur.ai/free/en/papers/kuwatly-2020-identifying-measuring-annotator-bias-based/)** *(2020 · 144 citations)* The paper asks whether the demographic profile of crowd annotators (gender, first language, age, education) leaves a measurable imprint on abusive-language labels and on the models trained from them. ## All works 6 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them. 1. [**ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education**Enkelejda Kasneci, Kathrin Seßler, Stefan Küchemann, et al.*2023 · 7,436 citations*](https://md.research.elamur.ai/free/en/papers/kasneci-2023-chatgpt-good-opportunities-challenges-large/) 2. [**Identifying and Measuring Annotator Bias Based on Annotators' Demographic Characteristics Proceedings of the Fourth Workshop on Online Abuse and Harms**Hala Al Kuwatly, Maximilian Wich, Georg Groh*2020 · 144 citations*](https://md.research.elamur.ai/free/en/papers/kuwatly-2020-identifying-measuring-annotator-bias-based/) 3. **[Language Models for German Text Simplification: Overcoming Parallel Data Scarcity through Style-specific Pre-training](https://aclanthology.org/2023.findings-acl.74/) Findings of the Association for Computational Linguistics: ACL 2023 · original ↗ · no summary yet**Miriam Anschütz et al.*2023 · 35 citations* 4. **[Introducing an Abusive Language Classification Framework for Telegram to Investigate the German Hater Community](https://arxiv.org/abs/2109.07346) arXiv:2109.07346 · original ↗ · no summary yet**Maximilian Wich et al.*2021 · 16 citations* 5. **[German Abusive Language Dataset with Focus on COVID-19](https://aclanthology.org/2021.konvens-1.26/) Proceedings of the 17th Conference on Natural Language Processing (KONVENS 2021) · original ↗ · no summary yet**Maximilian Wich, Svenja Räther, Georg Groh*2021 · 4 citations* 6. **[Estimating Grammar Correctness for a Priori Estimation of Machine Translation Post-Editing Effort](https://aclanthology.org/W14-0303/) Proceedings of the EACL 2014 Workshop on Humans and Computer-assisted Translation · original ↗ · no summary yet**Nicholas H. Kirk, Guchun Zhang, Georg Groh*2014* ## Co-authors here 1 co-author with a page, the most papers together first. - [Daryna Dementieva](https://md.research.elamur.ai/free/en/authors/daryna-dementieva/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - Findings of the Association for Computational Linguistics: ACL 2023 - Learning and Individual Differences - Proceedings of the 17th Conference on Natural Language Processing (KONVENS 2021) - Proceedings of the EACL 2014 Workshop on Humans and Computer-assisted Translation - Proceedings of the Fourth Workshop on Online Abuse and Harms ## Cited by Papers of our library cite their works 308 times (of the 141,840 papers whose bibliographies we read); [22 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/georg-groh/cited-by/). Updated 24 October 2026