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Irina Nikishina

Irina Nikishina has 2 papers in our library, in 2025–2026, most of them on Question answering, Evaluation & benchmarks, Information retrieval & search; often with Viktor Moskvoretskii, Alexander Panchenko, Artem Shelmanov.

2 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 7 · 62 works · 126 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 32 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #9013

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

🎓Universität HamburgHamburg · Germany2022–2026 · 28 paperscurrent🎓Skolkovo Institute of Science and TechnologySkolkovo · Russia2019–2022 · 15 papersEducation since 2019 · PhD, Computational and Data Science and Engineering🎓National Research University Higher School of EconomicsMoscow · Russia2017–2024 · 5 papersEducation 2017–2019 · master, Computational linguistics🔬Institute for System ProgrammingMoscow · Russia2018–2019 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

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

📚 Shelves 9The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksCognitive Neuroscience · 1 workExperimental and Cognitive Psychology · 1 workNeuroscience · 1 workPhilosophy · 1 workPsychology · 1 workArtificial Intelligence · 1 workComputer Science · 1 workLanguage and Linguistics · 1 work

🧭 Topics 3Research subjects and languages the work is about.Information retrieval & search · 1 workEvaluation & benchmarks · 1 workQuestion answering · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Adaptive Retrieval Without Self-Knowledge? Bringing Uncertainty Back Home (2025 · 21 citations)
    Adaptive retrieval lets an LLM decide for each question whether it needs external documents. The goal is to keep the accuracy benefits of RAG without paying for retrieval that is unnecessary or even misleading. Recent pipelines for this task are usually judged on answer quality and retrieval counts. They rarely…
  2. Argument-Based Comparative Question Answering Evaluation Benchmark (2026)
    Large language models can produce fluent answers to comparative questions such as "Simpsons or Family Guy?".

All works

4 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. Adaptive Retrieval Without Self-Knowledge? Bringing Uncertainty Back HomeAnnual Meeting of the Association for Computational Linguistics (ACL)Viktor Moskvoretskii, Maria Marina, Mikhail Salnikov, et al.2025 · 21 citations
  2. Are Large Language Models Good at Lexical Semantics? A Case of Taxonomy Learning ↗Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) · no summary yetViktor Moskvoretskii, Alexander Panchenko, Irina Nikishina2024 · 12 citations
  3. A Study on Manual and Automatic Evaluation for Text Style Transfer: The Case of Detoxification ↗Proceedings of the 2nd Workshop on Human Evaluation of NLP Systems (HumEval) · no summary yetVarvara Logacheva et al.2022 · 10 citations
  4. Argument-Based Comparative Question Answering Evaluation BenchmarkWorkshop on Argument MiningIrina Nikishina, Saba Anwar, Nikolay Dolgov, et al.2026

 Co-authors here

10 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 32 times (of the 149,439 papers whose bibliographies we read); 5 citing papers with a page here →.

Updated

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