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Andrianos Michail

Andrianos Michail has 4 papers in our library, in 2025–2026, most of them on Multilingual & cross-lingual NLP, Semantic parsing & meaning representation, Bias, fairness & safety; often with Juri Opitz, Simon Clematide, Rico Sennrich.

4 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 4 · 39 works · 48 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 96 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #10812

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

🎓University of ZurichZurich · Switzerland2023–2026 · 26 papersEmployment since 2023 · PhD Candidatecurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

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

📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 4 worksComputer Science · 4 worksArtificial Intelligence · 4 worksLanguage and Linguistics · 4 worksLiterature and Literary Theory · 1 workComputer Vision and Pattern Recognition · 1 workSafety Research · 1 workSocial Sciences · 1 work

🧭 Topics 3Research subjects and languages the work is about.Multilingual & cross-lingual NLP · 3 worksBias, fairness & safety · 1 workSemantic parsing & meaning representation · 1 work

 Works by year

2020s

20263 papers20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Adapting Multilingual Embedding Models to Historical Luxembourgish (2025 · 3 citations)
    Off-the-shelf multilingual sentence embeddings struggle with digitized historical Luxembourgish, a low-resource language.
  2. A Recipe for Adapting Multilingual Embedders to OCR-Error Robustness and Historical Texts (2026)
    Off-the-shelf multilingual embedding models work well on modern text but lose accuracy on digitized historical documents, where OCR mistakes and older spellings disrupt tokenization. The problem is worst for low-resource languages such as Luxembourgish, whose archives span about 150 years of shifting orthography.
  3. Information Representation Fairness in Long-Document Embeddings: The Peculiar Interaction of Positional and Language Bias (2026)
    Embedding-based search can only surface information that a document's vector actually encodes. This paper asks whether every part of a long, multi-segment document is represented equally. The authors build a permutation-based diagnostic on a comparable Wikipedia corpus in six languages. Topic-aligned articles are…
  4. Similar, but why? A Toolkit for Explaining Text Similarity (2026)
    Similarity scores from embedding models are hard to justify because they come from the interaction of two inputs, not from one.

All works

7 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

  1. PARAPHRASUS: A Comprehensive Benchmark for Evaluating Paraphrase Detection Models ↗Proceedings of the 31st International Conference on Computational Linguistics · no summary yetAndrianos Michail, Simon Clematide, Juri Opitz2025 · 5 citations
  2. Adapting Multilingual Embedding Models to Historical LuxembourgishWorkshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL)Andrianos Michail, Corina Raclé, Juri Opitz, et al.2025 · 3 citations
  3. Overview of HIPE-2026: Person-Place Relation Extraction from Multilingual Historical Texts ↗arXiv:2606.25935 · no summary yetJuri Opitz et al.2026 · 1 citation
  4. A Recipe for Adapting Multilingual Embedders to OCR-Error Robustness and Historical TextsLanguage Resources and Evaluation Conference (LREC)Andrianos Michail, Stylianos Psychias, Juri Opitz, et al.2026
  5. Information Representation Fairness in Long-Document Embeddings: The Peculiar Interaction of Positional and Language BiasFindings of the Association for Computational LinguisticsElias Schuhmacher, Andrianos Michail, Juri Opitz, et al.2026
  6. Similar, but why? A Toolkit for Explaining Text SimilarityConference of the European Chapter of the Association for Computational Linguistics (EACL)Juri Opitz, Andrianos Michail, Lucas Moeller, et al.2026
  7. Domain Adapted Text Summarization with Self-Generated Guidelines ↗Proceedings of the Natural Legal Language Processing Workshop 2025 · no summary yetAndrianos Michail et al.2025

 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 96 times (of the 149,439 papers whose bibliographies we read); 27 citing papers with a page here →.

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