---
title: "Who cites Mateusz Klimaszewski — 184 papers of our library"
description: "184 papers of the Elamur Research library cite the works of Mateusz Klimaszewski, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/mateusz-klimaszewski/cited-by/"
---
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# Who cites Mateusz Klimaszewski

198 citations of their works from 184 papers of our library (of the 149,439 whose bibliographies we read) · 50 with a page here, the most cited first · [← Mateusz Klimaszewski](https://md.research.elamur.ai/free/en/authors/mateusz-klimaszewski/)

1. **[Findings of the WMT25 General Machine Translation Shared Task: Time to Stop Evaluating on Easy Test Sets](https://md.research.elamur.ai/free/en/papers/kocmi-2025-findings-wmt25-general-machine-translation/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Tom Kocmi, Ekaterina Artemova, Eleftherios Avramidis, et al.*2025 · 73 citations*
2. **[Apertus: Democratizing Open and Compliant LLMs for Global Language Environments](https://md.research.elamur.ai/free/en/papers/cano-2026-apertus-democratizing-open-compliant-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.*2026 · 68 citations*
3. [**mmBERT: A Modern Multilingual Encoder with Annealed Language Learning arXiv:2509.06888**Marc Marone, Orion Weller, William Fleshman, et al.*2025 · 59 citations*](https://md.research.elamur.ai/free/en/papers/marone-2025-mmbert-modern-multilingual-encoder-annealed/)
4. [**EuroLLM-9B: Technical Report arXiv:2506.04079**Pedro Henrique Martins, Joao Alves, Patrick Fernandes, et al.*2025 · 45 citations*](https://md.research.elamur.ai/free/en/papers/martins-2025-eurollm-9b-technical-report/)
5. [**EuroBERT: Scaling Multilingual Encoders for European Languages arXiv:2503.05500**Nicolas Boizard, Hippolyte Gisserot-Boukhlef, Duarte M. Alves, et al.*2025 · 34 citations*](https://md.research.elamur.ai/free/en/papers/boizard-2025-eurobert-scaling-multilingual-encoders-european/)
6. **[LLäMmlein: Transparent, Compact and Competitive German-Only Language Models from Scratch](https://md.research.elamur.ai/free/en/papers/pfister-2025-llammlein-transparent-compact-competitive-german/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jan Pfister, Julia Wunderle, Andreas Hotho*2025 · 15 citations*
7. **[Scaling Low-Resource MT via Synthetic Data Generation with LLMs](https://md.research.elamur.ai/free/en/papers/gibert-2025-scaling-low-resource-mt-synthetic/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ona de Gibert, Joseph Attieh, Teemu Vahtola, et al.*2025 · 15 citations*
8. **[TurBLiMP: A Turkish Benchmark of Linguistic Minimal Pairs](https://md.research.elamur.ai/free/en/papers/basar-2025-turblimp-turkish-benchmark-linguistic-minimal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ezgi Başar, Francesca Padovani, Jaap Jumelet, et al.*2025 · 14 citations*
9. **[Parity-Aware Byte-Pair Encoding: Improving Cross-lingual Fairness in Tokenization](https://md.research.elamur.ai/free/en/papers/foroutan-2026-parity-aware-byte-pair-encoding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Negar Foroutan, Clara Meister, Debjit Paul, et al.*2026 · 12 citations*
10. **[From RAG to Agentic RAG for Faithful Islamic Question Answering](https://md.research.elamur.ai/free/en/papers/bhatia-2026-rag-agentic-rag-faithful-islamic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gagan Bhatia, Hamdy Mubarak, Mustafa Jarrar, et al.*2026 · 8 citations*
11. **[Localized Cultural Knowledge is Conserved and Controllable in Large Language Models](https://md.research.elamur.ai/free/en/papers/veselovsky-2026-localized-cultural-knowledge-is-conserved/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Veniamin Veselovsky, Berke Argın, Benedikt Stroebl, et al.*2026 · 7 citations*
12. **[Minimal Pair-Based Evaluation of Code-Switching](https://md.research.elamur.ai/free/en/papers/sterner-2025-minimal-pair-based-evaluation-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Igor Sterner, Simone Teufel*2025 · 6 citations*
13. **[Can Activation Steering Generalize Across Languages? A Study on Syllogistic Reasoning in Language Models](https://md.research.elamur.ai/free/en/papers/maraia-2026-can-activation-steering-generalize-across/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Gabriele Maraia, Leonardo Ranaldi, Marco Valentino, et al.*2026 · 5 citations*
14. [**Llama-GENBA-10B: A Trilingual Large Language Model for German, English and Bavarian arXiv:2509.05668**Michael Hoffmann, Jophin John, Stefan Schweter, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/hoffmann-2025-llama-genba-10b-trilingual-large/)
15. **[MELABenchv1: Benchmarking Large Language Models against Smaller Fine-Tuned Models for Low-Resource Maltese NLP](https://md.research.elamur.ai/free/en/papers/micallef-2025-melabenchv1-benchmarking-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kurt Micallef, Claudia Borg*2025 · 4 citations*
16. [**The Landscape of Arabic Large Language Models (ALLMs): A New Era for Arabic Language Technology arXiv:2506.01340**Shahad Al-Khalifa; Nadir Durrani; Hend Al-Khalifa;, Firoj Alam*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/al-khalifa-2025-landscape-arabic-large-language-models/)
17. **[Estonian WinoGrande Dataset: Comparative Analysis of LLM Performance on Human and Machine Translation](https://md.research.elamur.ai/free/en/papers/ojastu-2026-estonian-winogrande-dataset-comparative-analysis/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Marii Ojastu, Hele-Andra Kuulmets, Aleksei Dorkin, et al.*2026 · 3 citations*
18. **[Pretraining and Benchmarking Modern Encoders for Latvian](https://md.research.elamur.ai/free/en/papers/znotins-2026-pretraining-benchmarking-modern-encoders-latvian/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Arturs Znotins*2026 · 3 citations*
19. **[Testing Low-Resource Language Support in LLMs Using Language Proficiency Exams: the Case of Luxembourgish](https://md.research.elamur.ai/free/en/papers/lothritz-2025-testing-low-resource-language-support/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cedric Lothritz, Jordi Cabot, Laura Bernardy*2025 · 3 citations*
20. [**A Sovereign, Open-Source Foundation Model for German and English arXiv:2607.09424**Soofi-Team: Benedikt Droste, David Fitzek, Ruben Harle, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/droste-2026-sovereign-open-source-foundation-model/)
21. **[ALBA: A European Portuguese Benchmark for Evaluating Language and Linguistic Dimensions in Generative LLMs](https://md.research.elamur.ai/free/en/papers/vieira-2026-alba-european-portuguese-benchmark-evaluating/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Inês Vieira, Inês Calvo, Iago Paulo, et al.*2026 · 2 citations*
22. **[Current state of LLMs for Arabic dialectal machine translation](https://md.research.elamur.ai/free/en/papers/jon-2026-current-state-llms-arabic-dialectal/) [Workshop on NLP for Languages Using Arabic Script](https://md.research.elamur.ai/free/en/venues/abjadnlp/)**Josef Jon, Rawan Bondok, Ondřej Bojar*2026 · 2 citations*
23. **[PHEB: An European Portuguese High School-Level LLM Benchmark](https://md.research.elamur.ai/free/en/papers/tavares-2026-pheb-european-portuguese-high-school/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Diogo C. Tavares, Rafael Ferreira, Afonso Simplício, et al.*2026 · 2 citations*
24. **[AMALIA: A Fully Open Large Language Model for European Portuguese](https://md.research.elamur.ai/free/en/papers/simplicio-2026-amalia-fully-open-large-language/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Afonso Simplício, Gonçalo Vinagre, Miguel Moura Ramos, et al.*2026 · 1 citation*
25. **[Biases in Translation: Assessing Opinion Distortion in Machine Translated Texts](https://md.research.elamur.ai/free/en/papers/shafiabadi-2026-biases-translation-assessing-opinion-distortion/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Nazanin Shafiabadi, François Yvon*2026 · 1 citation*
26. **[Can LLMs Translate Italy's Language Varieties?](https://md.research.elamur.ai/free/en/papers/signoroni-2026-can-llms-translate-italy-s/) [Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT)](https://md.research.elamur.ai/free/en/venues/loresmt/)**Edoardo Signoroni, Pavel Rychlý*2026 · 1 citation*
27. **[CrowS-Pairs-NL: A Benchmark to Evaluate Dutch Stereotype Bias in LLMs](https://md.research.elamur.ai/free/en/papers/weide-2026-crows-pairs-nl-benchmark-evaluate/) [Workshop on Stereotypes Across Cultures in Language Technologies](https://md.research.elamur.ai/free/en/venues/stereacult/)**Jens van der Weide, Dong Nguyen, Marianne Schaaphok, et al.*2026 · 1 citation*
28. **[How Important is ‘Perfect' English for Machine Translation Prompts?](https://md.research.elamur.ai/free/en/papers/schmidtova-2026-how-important-is-perfect-english/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Patrícia Schmidtová, Niyati Bafna, Seth Aycock, et al.*2026 · 1 citation*
29. **[HPLT 3.0: Very Large-Scale Multilingual Resources for LLMs and MT. Mono- and Bi-lingual Data, Multilingual Evaluation, and Pre-Trained Models](https://md.research.elamur.ai/free/en/papers/oepen-2026-hplt-3-0-very-large/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Stephan Oepen, Nikolay Arefyev, Mikko Aulamo, et al.*2026 · 1 citation*
30. **[Improving Latvian Morphosyntactic Parsing with Pretrained Encoders and Analyzer-Constrained Decoding](https://md.research.elamur.ai/free/en/papers/znotins-2026-improving-latvian-morphosyntactic-parsing-pretrained/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Arturs Znotins*2026 · 1 citation*
31. [**KletterMix: Climbing Toward High-Quality German Pretraining Data - The Full Report arXiv:2606.03773**Maurice Kraus, Ruben Harle, Sebastian Sztwiertnia, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/kraus-2026-klettermix-climbing-toward-high-quality/)
32. **[Speak in Context: Multilingual ASR with Speech–Context Alignment via Contrastive Learning](https://md.research.elamur.ai/free/en/papers/zhang-2026-speak-context-multilingual-asr-speech/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yuchen Zhang, Haralambos Mouratidis, Ravi Shekhar*2026 · 1 citation*
33. **[Unlocking Latent Discourse Translation in LLMs Through Quality-Aware Decoding](https://md.research.elamur.ai/free/en/papers/mohammed-2026-unlocking-latent-discourse-translation-llms/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Wafaa Mohammed, Vlad Niculae, Chrysoula Zerva*2026 · 1 citation*
34. **[Vocab Diet: Reshaping the Vocabulary of LLMs via Vector Arithmetic](https://md.research.elamur.ai/free/en/papers/reif-2026-vocab-diet-reshaping-vocabulary-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuval Reif, Guy Kaplan, Roy Schwartz*2026 · 1 citation*
35. [**Mix, MinHash, and Match: Cross-Source Agreement for Multilingual Pretraining Datasets arXiv:2512.18834**Sultan Alrashed, Francesco Orabona*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alrashed-2025-mix-minhash-match-cross-source/)
36. **[Attribute-Controlled Translation with Preference Optimization](https://md.research.elamur.ai/free/en/papers/unanue-2026-attribute-controlled-translation-preference-optimization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Inigo Jauregi Unanue, Najmeh Sadoughi, Vimal Bhat, et al.*2026*
37. **[Beyond Simple Term Injection: Reasoning Models for Legal Translation in a Non-Dominant Language Variety](https://md.research.elamur.ai/free/en/papers/natale-2026-beyond-simple-term-injection-reasoning/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Paolo Di Natale, Elena Chiocchetti, Marlies Alber, et al.*2026*
38. **[Cultural and Knowledge Biases in LLMs through the Lens of Entity-Aware Machine Translation](https://md.research.elamur.ai/free/en/papers/xu-2026-cultural-knowledge-biases-llms-through/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Lu Xu, Luca Moroni, Roberto Navigli*2026*
39. **[EIFFEL: a novel benchmark to measure bias of English heavy training on French idiomatic expressions](https://md.research.elamur.ai/free/en/papers/noel-2026-eiffel-novel-benchmark-measure-bias/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Charlotte Noel, Nicholas Asher, Olivier Gouvert, et al.*2026*
40. **[Is Biomedical Specialization Still Worth It? Insights from Domain-Adaptive Language Modelling with a New French Health Corpus](https://md.research.elamur.ai/free/en/papers/mannion-2026-is-biomedical-specialization-still-worth/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aidan Mannion, Cécile Macaire, Armand Violle, et al.*2026*
41. [**LuxSQA: Ask Me in Luxembourgish with TTS-Augmented Spoken Question Answering arXiv:2607.02763**Nina Hosseini-Kivanani, Marco Matassoni, Alessio Brutti*2026*](https://md.research.elamur.ai/free/en/papers/hosseini-kivanani-2026-luxsqa-ask-me-luxembourgish-tts/)
42. [**MameLoshnLM: Yiddish Language Model and Evaluation Benchmark arXiv:2608.05850 · Proceedings of the Third Conference on Language Modeling (COLM 2026), 2026**Uri Katz, Omer Goldman, Tomasz Limisiewicz, et al.*2026*](https://md.research.elamur.ai/free/en/papers/katz-2026-mameloshnlm-yiddish-language-model-evaluation/)
43. **[Nanda Family: Open-Weights Generative Large Language Models for Hindi](https://md.research.elamur.ai/free/en/papers/singh-2026-nanda-family-open-weights-generative/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Aaryamonvikram Singh, Debopriyo Banerjee, Dhruv Sahnan, et al.*2026*
44. **[ParsCORE: The Persian Corpus of Online Registers](https://md.research.elamur.ai/free/en/papers/razzaghi-2026-parscore-persian-corpus-online-registers/) [Proceedings of the Workshop on NLP and LLMs for the Iranian Language Family](https://md.research.elamur.ai/free/en/venues/silkroadnlp/)**Alireza Razzaghi, Erik Henriksson, Veronika Laipalla*2026*
45. **[Quality and Appropriateness of Large Text Datasets for Irish NLP](https://md.research.elamur.ai/free/en/papers/walsh-2026-quality-appropriateness-large-text-datasets/) [SIGUL Joint Workshop with ELE, EURALI, and DCLRL: Towards Inclusivity and Equality: Language Resources and Technologies for Under-Resourced and Endangered Languages](https://md.research.elamur.ai/free/en/venues/sigul/)**Abigail Walsh, Mark Andrade, Jane Lauren Adkins, et al.*2026*
46. **[Reading Time in the Wild: An Assessment of Readability Predictors Based on Naturally-Observed Reading Times](https://md.research.elamur.ai/free/en/papers/vaals-2026-reading-time-wild-assessment-readability/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Sijbren van Vaals, Rik van Noord, Malvina Nissim*2026*
47. [**Repetition over Diversity: High-Signal Data Filtering for Sample-Efficient German Language Modeling arXiv:2604.28075**Ansar Aynetdinov, Patrick Haller, Alan Akbik*2026*](https://md.research.elamur.ai/free/en/papers/aynetdinov-2026-repetition-over-diversity-high-signal/)
48. **[Small Can Be Beautiful in LLMs for SSH: a Case for Bulgarian](https://md.research.elamur.ai/free/en/papers/simov-2026-small-can-be-beautiful-llms/) [Shaping Multilingual, Multimodal AI for the Social Sciences and Humanities @ LREC](https://md.research.elamur.ai/free/en/venues/llms4ssh/)**Kiril Simov, Nikolay Paev, Petya Osenova, et al.*2026*
49. **[The MaTOS Pipeline for the Translation of Scientific Abstracts on the HAL Platform](https://md.research.elamur.ai/free/en/papers/tsolakis-2026-matos-pipeline-translation-scientific-abstracts/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Panagiotis Tsolakis, Ziqian Peng, Laurent Romary, et al.*2026*
50. **[Why do Large Language Models Fail in Low-resource Translation? Unraveling the Token Dynamics of Large Language Models for Machine Translation](https://md.research.elamur.ai/free/en/papers/qian-2026-why-do-large-language-models/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Shenbin Qian, Yves Scherrer*2026*

134 more citing papers of our library have no page here yet.

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