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Who cites Tatiana Shavrina

1,574 citations of their works from 1,491 papers of our library (of the 149,439 whose bibliographies we read) · 323 with a page here, the most cited first · page 4 of 4 · 301–323 · ← Tatiana Shavrina

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  1. E-CONAN (Entailment, CONtradition And Neutral) Diagnostics Dataset Investigating Linguistic Phenomena in Arabic Natural Language UnderstandingarXiv:2609.33530Khloud AL Jallad, Nada Ghneim, Ghaida Rebdawi2026
  2. Few-shot Prompting or Supervised Tuning? A Comparative Study of LLMs for Linguistically Distant Language Pairs in BDILanguage Resources and Evaluation Conference (LREC)Deepen Naorem, Sanasam Ranbir Singh, Telem Joyson Singh, et al.2026
  3. HEBATRON: A Hebrew-Specialized Open-Weight Mixture-of-Experts Language ModelNoam Kayzer, Dan Revital, Ori Bar Joseph, et al.2026
  4. Language-Aware Token Boosting: LLM Language Confusion Reduction Without TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Trapoom Ukarapol, Pakhapoom Sarapat, Nut Chukamphaeng2026
  5. Learning Nested Named Entity Recognition from Flat AnnotationsConference of the European Chapter of the Association for Computational Linguistics (EACL)Igor Rozhkov, Natalia V Loukachevitch2026
  6. Merge and Conquer: Instructing Multilingual Models by Adding Target Language WeightsLanguage Resources and Evaluation Conference (LREC)Eneko Valero, Maria Ribalta i Albado, Oscar Sainz, et al.2026
  7. MUTANT: A Recipe for Multilingual Tokenizer DesignAnnual Meeting of the Association for Computational Linguistics (ACL)Souvik Rana, Ashish Kulkarni, Arul Menezes, et al.2026
  8. NASIMLab at SemEval-2026 Task 9: A Comparative Analysis of Fine-Tuned Small Language Models vs. Generative Large Language Models for Multilingual Polarization Type DetectionInternational Workshop on Semantic Evaluation (SemEval)Neel Sabhahit, Sanjeevan Selvaganapathy, Mehwish Nasim2026
  9. NorBERTo: A ModernBERT Model Trained for Portuguese with 331 Billion Tokens CorpusInternational Conference on Computational Processing of PortugueseEnzo S. N. Silva, Pablo B. Costa, Raphael C. Vlasman, et al.2026
  10. Parallel Universes, Parallel Languages: A Comprehensive Study on LLM-based Multilingual Counterfactual Example GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Qianli Wang, Van Bach Nguyen, Yihong Liu, et al.2026
  11. Probing the Dynamics of Syntactic Ability Acquisition Throughout LLM PretrainingHiroshi Matsuda, Masayuki Asahara2026
  12. Reading Time in the Wild: An Assessment of Readability Predictors Based on Naturally-Observed Reading TimesLanguage Resources and Evaluation Conference (LREC)Sijbren van Vaals, Rik van Noord, Malvina Nissim2026
  13. Russian Generative Spelling, Punctuation and Capitalization CorrectionLanguage Resources and Evaluation Conference (LREC)Nikita Martynov, Danil Astafurov, Ulyana Isaeva, et al.2026
  14. SiniticMTError: A Machine Translation Dataset with Error Annotations for Sinitic LanguagesLanguage Resources and Evaluation Conference (LREC)Hannah Liu, Junghyun Min, Annie En-Shiun Lee, et al.2026
  15. The Impact of Tokenization Algorithms on Hungarian Language Model PerformanceLanguage Resources and Evaluation Conference (LREC)Mátyás Osváth, Máté Norbert Molnár, Roland Gunics, et al.2026
  16. Transferring Scientific English Pre-Trained Language Models to Multiple Languages Using Cross-Lingual TransferNatural Scientific Language Processing (NSLP) @ LRECNikolas Rauscher, Fabio Barth, Georg Rehm2026
  17. Vinclat: Evaluating Reasoning, Cognition and Culture in One GameWorkshop on Multilingual Multicultural EvaluationMarc Pàmies, Javier Aula-Blasco, Aitor Gonzalez-Agirre, et al.2026
  18. What does Surprisal have to do with Information Status?Workshop on Research in Computational Linguistic Typology and Multilingual NLPAndrew Thomas Dyer2026
  19. What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge RepresentationsAnnual Meeting of the Association for Computational Linguistics (ACL)Yujie Luo, Zhuoyun Yu, Xuehai Wang, et al.2026
  20. Why do Large Language Models Fail in Low-resource Translation? Unraveling the Token Dynamics of Large Language Models for Machine TranslationAnnual Conference of the European Association for Machine Translation (EAMT)Shenbin Qian, Yves Scherrer2026
  21. WildSci: Advancing Scientific Reasoning from In-the-Wild LiteratureFindings of the Association for Computational LinguisticsTengxiao Liu, Deepak Nathani, Zekun Li, et al.2026
  22. Assessing the Agreement Competence of Large Language ModelsAlba Táboas García, Leo Wanner2025
  23. Survey on Key Technologies for Large Language Model Pre-training Systems (大语言模型预训练系统关键技术综述)Journal of SoftwareYanjie Gao (高彦杰), Yueguo Chen (陈跃国)2025

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