Achim Rettinger
Achim Rettinger has 5 papers in our library, in 2018–2026, most of them on Language models & pretraining, Knowledge graphs & ontologies; often with Simon Münker, Nils Schwager, Alistair Plum.
OpenAlex · ORCID · Wikidata · h-index 25 · 175 works · 1,902 citations OpenAlex, 2026-10-14
📄 5 works in our library · 🔗 Cited 39 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #4530
Affiliations
Fields, topics and concepts
📚 Shelves 10The field of science this work belongs to (OpenAlex fields).Computer Science · 5 worksDecision Sciences · 2 worksArtificial Intelligence · 5 worksManagement Science and Operations Research · 2 worksInformation Systems · 1 workArts and Humanities · 4 worksSocial Sciences · 4 worksGeneral Social Sciences · 4 worksLanguage and Linguistics · 4 worksSafety Research · 2 works
🧭 Topics 2Research subjects and languages the work is about.Knowledge graphs & ontologies · 1 workLanguage models & pretraining · 1 work
💡 Concepts 3Key ideas and methods explained on our concept pages.Knowledge graph · 1 workNatural language processing · 1 workOntology engineering · 1 work
Works by year
2020s
2010s
Papers
- Linked Data Quality of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO (2018 · 362 citations)
The large open cross-domain knowledge graphs (KGs) DBpedia, Freebase, OpenCyc, Wikidata and YAGO are widely used, yet no one has compared them thoroughly. - Don't Trust Generative Agents to Mimic Communication on Social Networks Unless You Benchmarked their Empirical Realism (2026 · 4 citations)
LLM-driven agents are increasingly used as stand-ins for people in computational social science. However, studies disagree on whether they reproduce human behaviour faithfully. The authors examine this for social networks, where simulation could reveal how platform design choices such as ranking or filtering affect… - Towards Simulating Social Media Users with LLMs: Evaluating the Operational Validity of Conditioned Comment Prediction (2026 · 1 citation)
The paper asks whether LLMs used as stand-ins for real people in social science can reproduce how specific individuals behave online, rather than just producing comments that look plausible. - Challenging the Myth: A Research Arc on LLMs as Human Simulacra (2026)
This position-style paper examines a popular assumption in computational social science: that off-the-shelf, instruction-tuned open-source LLMs, given only light prompting, can stand in for human participants. - Next Reply Prediction X (NRP-X) Dataset: Linguistic Discrepancies in Naively Generated Content (2026)
Social scientists increasingly use LLMs as stand-ins for human participants. When models are simply prompted without behavioral constraints, their writing may differ from real users' in ways that undermine research validity. The authors build NRP-X, a resource for testing this on authentic X (formerly Twitter) data…
All works
- Linked Data Quality of DBpedia, Freebase, OpenCyc, Wikidata, and YAGOSemantic WebMichael Färber, Frederic Bartscherer, Carsten Menne, et al.2018 · 362 citations
- Bilingual Word Embeddings from Parallel and Non-parallel Corpora for Cross-Language Text Classification ↗Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yetAditya Mogadala, Achim Rettinger2016 · 97 citations
- Zero-shot prompt-based classification: topic labeling in times of foundation models in German Tweets ↗Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop) · no summary yetSimon Münker, Kai Kugler, Achim Rettinger2025 · 5 citations
- Don't Trust Generative Agents to Mimic Communication on Social Networks Unless You Benchmarked their Empirical RealismConference of the European Chapter of the Association for Computational Linguistics (EACL)Simon Münker, Nils Schwager, Achim Rettinger2026 · 4 citations
- Towards Simulating Social Media Users with LLMs: Evaluating the Operational Validity of Conditioned Comment PredictionWorkshop on Computational Approaches to Subjectivity, Sentiment and Social Media AnalysisNils Schwager, Simon Münker, Alistair Plum, et al.2026 · 1 citation
- Challenging the Myth: A Research Arc on LLMs as Human SimulacraBig Picture v2: Crafting a Research NarrativeSimon Münker, Achim Rettinger, Damian Trilling2026
- Next Reply Prediction X (NRP-X) Dataset: Linguistic Discrepancies in Naively Generated ContentShaping Multilingual, Multimodal AI for the Social Sciences and Humanities @ LRECSimon Münker, Nils Schwager, Kai Kugler, et al.2026
Co-authors here
Venues
- Big Picture v2: Crafting a Research Narrative: Big Picture v2: Crafting a Research Narrative 2026
- Conference of the European Chapter of the Association for Computational Linguistics (EACL): EACL 2026
- Shaping Multilingual, Multimodal AI for the Social Sciences and Humanities @ LREC: Shaping Multilingual, Multimodal AI for the Social Sciences and Humanities @ LREC 2026
- Semantic Web: Semantic Web 2018
- Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis: Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis 2026
- Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
- Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
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