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Mykola Pechenizkiy

Mykola Pechenizkiy has 2 papers in our library, in 2024–2026, most of them on Language models & pretraining, Multilingual & cross-lingual NLP, Reasoning; often with Meng Fang, Jun Wang, Ling Chen.

2 papers in our library · 2024–2026

OpenAlex · ORCID · Wikidata · h-index 42 · 445 works · 11,869 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 15 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #10288

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

🎓Eindhoven University of TechnologyEindhoven · Netherlands2007–2026 · 298 papersEmploymentcurrent🏛️National Research and Innovation AgencyJakarta · Indonesia2023–2026 · 2 paperscurrent🎓University of LiverpoolLiverpool · United Kingdom2023–2026 · 2 paperscurrent🎓University of JyväskyläJyväskylä · Finland2003–2022 · 36 papers🎓University of TwenteEnschede · Netherlands2021–2022 · 2 papers
🏛️Technische Universiteit Eindhoven Faculteit Wiskunde en InformaticaEindhoven · Netherlands2006Employment since 2006 · Professor, Computer Science

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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).Artificial Intelligence · 2 worksComputer Science · 2 worksArts and Humanities · 1 workComputational Theory and Mathematics · 1 workLanguage and Linguistics · 1 work

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 1 workMultilingual & cross-lingual NLP · 1 workReasoning · 1 work

 Works by year

2020s

20261 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Large Language Models Are Neurosymbolic Reasoners (2024 · 34 citations)
    The paper asks whether general-purpose LLMs can serve as symbolic reasoners without task-specific training.
  2. MATH-IDN: A Multilingual Mathematical Problem Solving Dataset Featuring Local Languages in Indonesia (2026)
    LLMs perform well on English math benchmarks, but little is known about how they handle Indonesia's local languages, and existing multilingual math sets leave them out.

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. Large Language Models Are Neurosymbolic ReasonersProceedings of the AAAI Conference on Artificial IntelligenceMeng Fang, Shilong Deng, Yudi Zhang, et al.2024 · 34 citations
  2. MATH-IDN: A Multilingual Mathematical Problem Solving Dataset Featuring Local Languages in IndonesiaFindings of the Association for Computational LinguisticsXiao Xiao, Iftitahu Ni'mah, Yuyun Wabula, et al.2026
  3. Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data ↗arXiv:2411.09431 · no summary yetRik Raes, Saskia Lensink, Mykola Pechenizkiy2024

 Co-authors here

5 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 15 times (of the 149,439 papers whose bibliographies we read); 6 citing papers with a page here →.

Updated

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