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Paweł Morawiecki

Paweł Morawiecki has 2 papers in our library, in 2018–2026, most of them on Coreference resolution, Language models & pretraining, Evaluation & benchmarks; often with Łukasz Borchmann, Maciej Ogrodniczuk.

2 papers in our library · 2018–2026

OpenAlex · ORCID · h-index 13 · 48 works · 611 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 6 times in our library · ⭐ Paper Stars ranking: #9096

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

🏛️Polish Academy of SciencesWarsaw · Poland2010–2026 · 30 paperscurrent🔬Institute of Computer ScienceWarsaw · Poland2010–2026 · 21 paperscurrent🎓Warsaw University of TechnologyWarsaw · Poland2004–2015 · 3 papers🎓Kielce University of TechnologyKielce · Poland2007–2008 · 2 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 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work

🧭 Topics 3Research subjects and languages the work is about.Coreference resolution · 1 workEvaluation & benchmarks · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20261 paper

2010s

20181 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Deep Neural Networks for Coreference Resolution for Polish (2018 · 19 citations)
    This work presents the first coreference resolver for Polish built on deep neural networks. Coreference resolution means grouping text fragments that point to the same discourse entity. The authors train a feed-forward classifier that scores pairs of mentions and returns the probability that they corefer. Mentions…
  2. Can Models Help Us Create Better Models? Evaluating LLMs as Data Scientists (2026 · 1 citation)
    Most LLM benchmarks test knowledge recall or ask a model to turn a clear specification into code. Few check whether a model can decide for itself which data transformations would make a predictive model stronger. The authors introduce FeatEng, a benchmark that treats feature engineering on tabular data as a…

 Co-authors here

2 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 6 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

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