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Tomasz Limisiewicz

Tomasz Limisiewicz has 5 papers in our library, in 2023–2026, most of them on Language models & pretraining, Multilingual & cross-lingual NLP, Bias, fairness & safety; often with Hila Gonen, Noah A. Smith, Luke Zettlemoyer.

5 papers in our library · 2023–2026

OpenAlex · h-index 7 · 45 works · 1,007 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 1,407 times in our library · 6 more in our library without a page yet · ⭐ Paper Stars ranking: #6806

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 WashingtonSeattle · United States2026 · 6 paperscurrent🎓Charles UniversityPrague · Czechia2020–2025 · 19 papers🎓Hebrew University of JerusalemJerusalem · Israel2022–2023 · 4 papers

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 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 5 worksArts and Humanities · 5 worksComputer Science · 5 worksLanguage and Linguistics · 5 worksSafety Research · 2 worksSocial Sciences · 2 works

🧭 Topics 8Research subjects and languages the work is about.Language models & pretraining · 4 worksMultilingual & cross-lingual NLP · 3 worksBias, fairness & safety · 2 worksMorphology · 1 workTokenization & segmentation · 1 workEvaluation & benchmarks · 1 workHebrew & Aramaic · 1 workSemitic languages · 1 work

 Works by year

2020s

20261 paper20243 papers20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Breaking the Curse of Multilinguality with Cross-lingual Expert Language Models (2024 · 42 citations)
    Multilingual language models fit many languages into one fixed set of parameters, so each language usually ends up weaker than it would be in a dedicated monolingual model.
  2. MYTE: Morphology-Driven Byte Encoding for Better and Fairer Multilingual Language Modeling (2024 · 30 citations)
    Byte-level multilingual language models avoid the coverage gaps of subword vocabularies, but they inherit a bias built into UTF-8.
  3. MAGNET: Improving the Multilingual Fairness of Language Models with Adaptive Gradient-Based Tokenization (2024 · 19 citations)
    Byte-level and subword language models usually split non-Latin-script text into many more pieces than English.
  4. Debiasing Algorithm through Model Adaptation (2023 · 10 citations)
    Large language models such as LLaMA absorb gender stereotypes from their training data, for example linking occupations like mechanic or nurse with one gender.
  5. MameLoshnLM: Yiddish Language Model and Evaluation Benchmark (2026)
    Yiddish has a long written tradition but a small and unreliable presence on the web, so multilingual models handle it poorly and there are few trustworthy ways to measure them.

All works

11 works of theirs in our library, the most cited first; 5 with a page here, the others link their original until we summarise them.

  1. BLOOM: A 176B-Parameter Open-Access Multilingual Language Model ↗arXiv:2211.05100 · no summary yetBigScience Workshop et al.2022 · 1,606 citations
  2. Breaking the Curse of Multilinguality with Cross-lingual Expert Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Terra Blevins, Tomasz Limisiewicz, Suchin Gururangan, et al.2024 · 42 citations
  3. MYTE: Morphology-Driven Byte Encoding for Better and Fairer Multilingual Language ModelingAnnual Meeting of the Association for Computational Linguistics (ACL)Tomasz Limisiewicz, Terra Blevins, Hila Gonen, et al.2024 · 30 citations
  4. MAGNET: Improving the Multilingual Fairness of Language Models with Adaptive Gradient-Based TokenizationConference on Neural Information Processing Systems (NeurIPS)Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.2024 · 19 citations
  5. Debiasing Algorithm through Model AdaptationarXiv:2310.18913Tomasz Limisiewicz, David Mareček, Tomaš Musil2023 · 10 citations
  6. Fast Byte Latent Transformer ↗arXiv (Cornell University) · no summary yetJulie Kallini et al.2026 · 1 citation
  7. Compute Optimal Tokenization ↗arXiv (Cornell University) · no summary yetTomasz Limisiewicz et al.2026 · 1 citation
  8. Retrofitting language models to operate over bytes ↗Nature · no summary yetBenjamin Minixhofer et al.2026 · 1 citation
  9. MameLoshnLM: Yiddish Language Model and Evaluation BenchmarkarXiv:2608.05850 · Proceedings of the Third Conference on Language Modeling (COLM 2026), 2026Uri Katz, Omer Goldman, Tomasz Limisiewicz, et al.2026
  10. Breaking the Token Ceiling: Distilling Smaller, Stronger Byte Models ↗arXiv (Cornell University) · no summary yetKalyani Marathe et al.2026
  11. Last Translation Benchmark ↗arXiv:2609.04173 · no summary yetVilem Zouhar et al.2026

 Co-authors here

12 of 13 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 1,407 times (of the 149,439 papers whose bibliographies we read); 300 citing papers with a page here →.

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