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Ulrich Schäfer

Ulrich Schäfer has 2 papers in our library, in 2012–2026, most of them on Coreference resolution, Bias, fairness & safety.

2 papers in our library · 2012–2026

OpenAlex · ORCID · h-index 15 · 62 works · 898 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 13 times in our library · ⭐ Paper Stars ranking: #8180

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Ostbayerische Technische Hochschule Amberg-WeidenAmberg · Germany2017–2026 · 15 paperscurrent🔬German Research Centre for Artificial IntelligenceKaiserslautern · Germany1994–2013 · 30 papers🎓Saarland UniversitySaarbrücken · Germany2004–2006 · 3 papers🎓University of RegensburgRegensburg · Germany2023–2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 2Research subjects and languages the work is about.Coreference resolution · 1 workBias, fairness & safety · 1 work

 Works by year

2020s

20261 paper

2010s

20121 paper

 Papers

The most cited first (OpenAlex and our library).

  1. A Fully Coreference-annotated Corpus of Scholarly Papers from the ACL Anthology (2012 · 38 citations)
    Most coreference resolution (CR) research and training data, such as MUC and ACE, come from newswire. The authors found that systems trained on news perform worse on scientific writing, which relies more on definite descriptions, domain terminology and abstract entities than on person or organization names. To fill…
  2. Detection of Adversarial Prompts with Model Predictive Entropy (2026)
    Safety-aligned LLMs can still be jailbroken. Many existing defenses depend on knowing the attack type in advance, on retraining, or on a separate guard model. The authors present SENTRY (Semantic ENtropy-based attack Recognition sYstem), an attack-agnostic detector that looks at how uncertain the model is when it…

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 13 times (of the 149,439 papers whose bibliographies we read); 6 citing papers with a page here →.

Updated

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