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Mehdi Ali

Mehdi Ali has 2 papers in our library, in 2024–2026, most of them on Language models & pretraining, Multilingual & cross-lingual NLP, Tokenization & segmentation; often with Michael Fromm, Abbas Goher Khan, Jan Ebert.

2 papers in our library · 2024–2026

OpenAlex · ORCID · Wikidata · h-index 9 · 36 works · 392 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 93 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #6751

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

🔬Fraunhofer Institute for Intelligent Analysis and Information SystemsSankt Augustin · Germany2019–2026 · 18 paperscurrent🎓University of BonnBonn · Germany2018–2022 · 13 papersEmployment since 2018🔬Lamarr Institute for Machine Learning and Artificial IntelligenceSankt Augustin · Germany2023–2025 · 11 papers🔬Fraunhofer Institute for Algorithms and Scientific ComputingSankt Augustin · Germany2015–2018Employment 2015–2018

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 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 3Research subjects and languages the work is about.Language models & pretraining · 2 worksMultilingual & cross-lingual NLP · 1 workTokenization & segmentation · 1 work

💡 Concepts 2Key ideas and methods explained on our concept pages.Subword tokenization · 1 workTokenization · 1 work

 Works by year

2020s

20261 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Tokenizer Choice For LLM Training: Negligible or Crucial? (2024 · 104 citations)
    Tokenizers are rarely examined when building LLMs. This paper asks whether the choice of tokenizer measurably affects decoder-only model quality and training cost, in both English-only and multilingual settings. The authors built two training corpora of 70B words each, with matched domain mixtures (80% web-crawled…
  2. KletterMix: Climbing Toward High-Quality German Pretraining Data - The Full Report (2026 · 1 citation)
    Open German pretraining data still trails English. Native German collections are usually smaller, noisier, less documented, and seldom tested by actually training models on them. The authors take a different route: instead of crawling more German web text, they machine-translate a strong English mixture, ClimbMix…

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. Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework ↗arXiv:2006.13365 · no summary yetMehdi Ali et al.2020 · 142 citations
  2. Tokenizer Choice For LLM Training: Negligible or Crucial?Findings of the Association for Computational LinguisticsMehdi Ali, Michael Fromm, Klaudia Thellmann, et al.2024 · 104 citations
  3. KletterMix: Climbing Toward High-Quality German Pretraining Data - The Full ReportarXiv:2606.03773Maurice Kraus, Ruben Harle, Sebastian Sztwiertnia, et al.2026 · 1 citation

 Co-authors here

11 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 93 times (of the 149,439 papers whose bibliographies we read); 28 citing papers with a page here →.

Updated

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