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Christopher Hahn

Christopher Hahn has 2 papers in our library, in 2020–2024; often with Abhinav Lalwani, Markus N. Rabe, Mrinmaya Sachan.

2 papers in our library · 2020–2024

OpenAlex · ORCID · Wikidata · h-index 13 · 31 works · 448 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 36 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #10074

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

🎓Johns Hopkins UniversityBaltimore · United States2025 · 1 papercurrent🎓Saarland UniversitySaarbrücken · Germany2017–2020 · 16 papers🔬Helmholtz Center for Information SecuritySaarbrücken · Germany2020–2022 · 5 papers🎓Stanford UniversityStanford · United States2021–2023 · 4 papers🎓Technische Universität DresdenDresden · Germany2021 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 more institutions on single bylines are not listed.

 Fields, topics and concepts

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

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksComputational Theory and Mathematics · 1 workArts and Humanities · 1 workLanguage and Linguistics · 1 work

 Works by year

2020s

20241 paper20201 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Teaching Temporal Logics to Neural Networks (2020 · 24 citations)
    The paper tests two things. First, can a neural network solve a hard logical task end to end? Second, does it learn what the logic means, or does it only copy the tool that produced its training data? The task is finding a satisfying trace for a formula in linear-time temporal logic (LTL), a core problem in…
  2. Autoformalizing Natural Language to First-Order Logic: A Case Study in Logical Fallacy Detection (2024 · 15 citations)
    The paper addresses automatically translating ordinary-language arguments into First-Order Logic (FOL) so that symbolic tools can check whether they actually hold.

All works

3 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. Teaching Temporal Logics to Neural NetworksarXiv:2003.04218Christopher Hahn, Frederik Schmitt, Jens U. Kreber, et al.2020 · 24 citations
  2. Autoformalizing Natural Language to First-Order Logic: A Case Study in Logical Fallacy DetectionarXiv:2405.02318Abhinav Lalwani, Tasha Kim, Lovish Chopra, et al.2024 · 15 citations
  3. LawInstruct: A Resource for Studying Language Model Adaptation to the Legal Domain ↗Findings of the Association for Computational Linguistics: NAACL 2025 · no summary yetJoel Niklaus et al.2025 · 12 citations

 Co-authors here

4 co-authors with a page, the most papers together first.

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 36 times (of the 149,439 papers whose bibliographies we read); 15 citing papers with a page here →.

Updated

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