---
title: "Who cites Vladislav Mikhailov — 238 papers of our library"
description: "238 papers of the Elamur Research library cite the works of Vladislav Mikhailov, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/vladislav-mikhailov/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/vladislav-mikhailov/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Vladislav Mikhailov](https://md.research.elamur.ai/free/en/authors/vladislav-mikhailov/) / cited by

# Who cites Vladislav Mikhailov

258 citations of their works from 238 papers of our library (of the 149,439 whose bibliographies we read) · 69 with a page here, the most cited first · [← Vladislav Mikhailov](https://md.research.elamur.ai/free/en/authors/vladislav-mikhailov/)

1. [**Crosslingual Generalization through Multitask Finetuning arXiv:2211.01786**Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.*2022 · 703 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/)
2. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
3. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model arXiv:2402.07827**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 253 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/)
4. **[In-context Examples Selection for Machine Translation](https://md.research.elamur.ai/free/en/papers/agrawal-2023-context-examples-selection-machine-translation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sweta Agrawal, Chunting Zhou, Mike Lewis, et al.*2023 · 243 citations*
5. [**mGPT: Few-Shot Learners Go Multilingual arXiv:2204.07580**Oleh Shliazhko, Alena Fenogenova, Maria Tikhonova, et al.*2022 · 203 citations*](https://md.research.elamur.ai/free/en/papers/shliazhko-2022-mgpt-few-shot-learners-go/)
6. **[Do Llamas Work in English? On the Latent Language of Multilingual Transformers](https://md.research.elamur.ai/free/en/papers/wendler-2024-do-llamas-work-english-latent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chris Wendler, Veniamin Veselovsky, Giovanni Monea, et al.*2024 · 177 citations*
7. **[Testing the Predictions of Surprisal Theory in 11 Languages](https://md.research.elamur.ai/free/en/papers/wilcox-2023-testing-predictions-surprisal-theory-11/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ethan G. Wilcox, Tiago Pimentel, Clara Meister, et al.*2023 · 159 citations*
8. [**Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature arXiv:2310.05130**Guangsheng Bao, Yanbin Zhao, Zhiyang Teng, et al.*2023 · 148 citations*](https://md.research.elamur.ai/free/en/papers/bao-2023-fast-detectgpt-efficient-zero-shot/)
9. **[Tokenizer Choice For LLM Training: Negligible or Crucial?](https://md.research.elamur.ai/free/en/papers/ali-2024-tokenizer-choice-llm-training-negligible/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mehdi Ali, Michael Fromm, Klaudia Thellmann, et al.*2024 · 104 citations*
10. **[BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting](https://md.research.elamur.ai/free/en/papers/yong-2023-bloom-1-adding-language-support/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zheng Xin Yong, Hailey Schoelkopf, Niklas Muennighoff, et al.*2023 · 102 citations*
11. **[Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable Survey](https://md.research.elamur.ai/free/en/papers/kumar-2023-language-generation-models-can-cause/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sachin Kumar, Vidhisha Balachandran, Lucille Njoo, et al.*2023 · 90 citations*
12. **[A Family of Pretrained Transformer Language Models for Russian](https://md.research.elamur.ai/free/en/papers/zmitrovich-2024-family-pretrained-transformer-language-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Dmitry Zmitrovich, Aleksandr Abramov, Andrey Kalmykov, et al.*2024 · 60 citations*
13. [**MaLA-500: Massive Language Adaptation of Large Language Models arXiv:2401.13303**Peiqin Lin, Shaoxiong Ji, Jorg Tiedemann, et al.*2024 · 58 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-mala-500-massive-language-adaptation/)
14. **[How to Compute the Probability of a Word](https://md.research.elamur.ai/free/en/papers/pimentel-2024-how-compute-probability-word/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tiago Pimentel, Clara Meister*2024 · 38 citations*
15. **[JASMINE: Arabic GPT Models for Few-Shot Learning](https://md.research.elamur.ai/free/en/papers/nagoudi-2023-jasmine-arabic-gpt-models-few/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**El Moatez Billah Nagoudi, Muhammad Abdul-Mageed, AbdelRahim Elmadany, et al.*2023 · 38 citations*
16. [**Efficient Language Model Training through Cross-Lingual and Progressive Transfer Learning arXiv:2301.09626**Malte Ostendorff, Georg Rehm*2023 · 36 citations*](https://md.research.elamur.ai/free/en/papers/ostendorff-2023-efficient-language-model-training-through/)
17. **[People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated text](https://md.research.elamur.ai/free/en/papers/russell-2025-people-who-frequently-use-chatgpt/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jenna Russell, Marzena Karpinska, Mohit Iyyer*2025 · 33 citations*
18. [**Nemotron-4 15B Technical Report arXiv:2402.16819**Jupinder Parmar, Shrimai Prabhumoye, Joseph Jennings, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/parmar-2024-nemotron-4-15b-technical-report/)
19. **[IberoBench: A Benchmark for LLM Evaluation in Iberian Languages](https://md.research.elamur.ai/free/en/papers/baucells-2025-iberobench-benchmark-llm-evaluation-iberian/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Irene Baucells, Javier Aula-Blasco, Iria de-Dios-Flores, et al.*2025 · 24 citations*
20. **[A Survey of Large Language Models for Arabic Language and its Dialects](https://md.research.elamur.ai/free/en/papers/mashaabi-2024-survey-large-language-models-arabic/) [ACM Transactions on Asian and Low-Resource Language Information Processing](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-asian-and-low-resource-language-information-processing/)**Malak Mashaabi, Shahad Al-Khalifa, Hend Al-Khalifa*2024 · 24 citations*
21. **[An Expanded Massive Multilingual Dataset for High-Performance Language Technologies (HPLT)](https://md.research.elamur.ai/free/en/papers/burchell-2025-expanded-massive-multilingual-dataset-high/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Laurie Burchell, Ona de Gibert, Nikolay Arefyev, et al.*2025 · 23 citations*
22. [**Efficiently Adapting Pretrained Language Models To New Languages arXiv:2311.05741**Zoltan Csaki, Pian Pawakapan, Urmish Thakker, et al.*2023 · 21 citations*](https://md.research.elamur.ai/free/en/papers/csaki-2023-efficiently-adapting-pretrained-language-models/)
23. [**ModuleFormer: Modularity Emerges from Mixture-of-Experts arXiv:2306.04640**Yikang Shen, Zheyu Zhang, Tianyou Cao, et al.*2023 · 21 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-moduleformer-modularity-emerges-mixture-experts/)
24. **[What Drives Performance in Multilingual Language Models?](https://md.research.elamur.ai/free/en/papers/nezhad-2024-drives-performance-multilingual-language-models/) [Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial)](https://md.research.elamur.ai/free/en/venues/vardial/)**Sina Bagheri Nezhad, Ameeta Agrawal*2024 · 20 citations*
25. **[The Russian-focused embedders' exploration: ruMTEB benchmark and Russian embedding model design](https://md.research.elamur.ai/free/en/papers/snegirev-2025-russian-focused-embedders-exploration-rumteb/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Artem Snegirev, Maria Tikhonova, Maksimova Anna, et al.*2025 · 19 citations*
26. **[ActiveLLM: Large Language Model-Based Active Learning for Textual Few-Shot Scenarios](https://md.research.elamur.ai/free/en/papers/bayer-2026-activellm-large-language-model-based/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Markus Bayer, Justin Lutz, Christian Reuter*2026 · 16 citations*
27. **[Analyzing and Adapting Large Language Models for Few-Shot Multilingual NLU: Are We There Yet?](https://md.research.elamur.ai/free/en/papers/razumovskaia-2025-analyzing-adapting-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Evgeniia Razumovskaia, Ivan Vulić, Anna Korhonen*2025 · 15 citations*
28. **[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*
29. **[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*
30. **[How Transliterations Improve Crosslingual Alignment](https://md.research.elamur.ai/free/en/papers/liu-2025-how-transliterations-improve-crosslingual-alignment/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yihong Liu, Mingyang Wang, Amir Hossein Kargaran, et al.*2025 · 12 citations*
31. [**Multilingual Arbitrage: Optimizing Data Pools to Accelerate Multilingual Progress arXiv:2408.14960**Ayomide Odumakinde, Daniel D'souza, Pat Verga, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/odumakinde-2024-multilingual-arbitrage-optimizing-data-pools/)
32. **[Anything Goes? A Crosslinguistic Study of (Im)possible Language Learning in LMs](https://md.research.elamur.ai/free/en/papers/yang-2025-anything-goes-crosslinguistic-study-im/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiulin Yang, Tatsuya Aoyama, Yuekun Yao, et al.*2025 · 8 citations*
33. **[NorEval: A Norwegian Language Understanding and Generation Evaluation Benchmark](https://md.research.elamur.ai/free/en/papers/mikhailov-2025-noreval-norwegian-language-understanding-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Vladislav Mikhailov, Tita Enstad, David Samuel, et al.*2025 · 7 citations*
34. **[Paramanu: Compact and Competitive Monolingual Language Models for Low-Resource Morphologically Rich Indian Languages](https://md.research.elamur.ai/free/en/papers/niyogi-2026-paramanu-compact-competitive-monolingual-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mitodru Niyogi, Eric Gaussier, Arnab Bhattacharya*2026 · 5 citations*
35. **[A Collection of Question Answering Datasets for Norwegian](https://md.research.elamur.ai/free/en/papers/mikhailov-2025-collection-question-answering-datasets-norwegian/) [Nordic Conference on Computational Linguistics (NoDaLiDa)](https://md.research.elamur.ai/free/en/venues/nodalida/)**Vladislav Mikhailov, Petter Mæhlum, Victoria Ovedie Chruickshank Langø, et al.*2025 · 5 citations*
36. **[Teaching Old Tokenizers New Words: Efficient Tokenizer Adaptation for Pretrained Models](https://md.research.elamur.ai/free/en/papers/purason-2026-teaching-old-tokenizers-new-words/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Taido Purason, Pavel Chizhov, Ivan P. Yamshchikov, et al.*2026 · 4 citations*
37. **[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*
38. **[Multilingual Nonce Dependency Treebanks: Understanding how Language Models Represent and Process Syntactic Structure](https://md.research.elamur.ai/free/en/papers/arps-2024-multilingual-nonce-dependency-treebanks-understanding/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**David Arps, Laura Kallmeyer, Younes Samih, et al.*2024 · 4 citations*
39. **[Performance Implications of Using Unrepresentative Corpora in Arabic Natural Language Processing](https://md.research.elamur.ai/free/en/papers/alshahrani-2023-performance-implications-unrepresentative-corpora-arabic/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Saied Alshahrani, Norah Alshahrani, Soumyabrata Dey, et al.*2023 · 4 citations*
40. **[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*
41. [**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/)
42. **[T-pro 2.0: An Efficient Russian Hybrid-Reasoning Model and Playground](https://md.research.elamur.ai/free/en/papers/stoianov-2026-t-pro-2-0-efficient/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Dmitrii Stoianov, Danil Taranets, Olga Tsymboi, et al.*2026 · 2 citations*
43. **[Do LLMs Really Memorize Personally Identifiable Information? Revisiting PII Leakage with a Cue-Controlled Memorization Framework](https://md.research.elamur.ai/free/en/papers/luo-2026-do-llms-really-memorize-personally/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyu Luo, Yiyi Chen, Qiongxiu Li, et al.*2026 · 1 citation*
44. **[Frankentext: Stitching random text fragments into long-form narratives](https://md.research.elamur.ai/free/en/papers/pham-2026-frankentext-stitching-random-text-fragments/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chau Minh Pham, Jenna Russell, Dzung Pham, et al.*2026 · 1 citation*
45. **[How multilingual are multilingual LLMs? A case study in Northern Sámi-Finnish Translation](https://md.research.elamur.ai/free/en/papers/saleva-2026-how-multilingual-are-multilingual-llms/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Jonne Sälevä, Constantine Lignos*2026 · 1 citation*
46. **[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*
47. **[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*
48. **[Probing for Reading Times](https://md.research.elamur.ai/free/en/papers/tsipidi-2026-probing-reading-times/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Eleftheria Tsipidi, Samuel Kiegeland, Francesco Ignazio Re, et al.*2026 · 1 citation*
49. **[Reformulate and Create, Don't Translate: Creating Natural Prompts for Underserved Languages](https://md.research.elamur.ai/free/en/papers/simonsen-2026-reformulate-create-don-t-translate/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Annika Simonsen, Mathias Stenlund, Lars Bungum, et al.*2026 · 1 citation*
50. [**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/)
51. **[CEAID: Benchmark of Multilingual Machine-Generated Text Detection Methods for Central European Languages](https://md.research.elamur.ai/free/en/papers/macko-2026-ceaid-benchmark-multilingual-machine-generated/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dominik Macko, Jakub Kopál*2026*
52. **[E-CONAN (Entailment, CONtradition And Neutral) Benchmarks: Arabic Textual Entailment and Natural Inference Datasets](https://md.research.elamur.ai/free/en/papers/jallad-2026-e-conan-entailment-contradition-neutral-benchmarks/) [IEEE Access](https://md.research.elamur.ai/free/en/venues/ieee-access/)**Khloud AL Jallad, Nada Ghneim, Ghaida Rebdawi*2026*
53. [**E-CONAN (Entailment, CONtradition And Neutral) Diagnostics Dataset Investigating Linguistic Phenomena in Arabic Natural Language Understanding arXiv:2609.33530**Khloud AL Jallad, Nada Ghneim, Ghaida Rebdawi*2026*](https://md.research.elamur.ai/free/en/papers/jallad-2026-e-conan-entailment-contradition-neutral/)
54. **[Few-shot Prompting or Supervised Tuning? A Comparative Study of LLMs for Linguistically Distant Language Pairs in BDI](https://md.research.elamur.ai/free/en/papers/naorem-2026-few-shot-prompting-or-supervised/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Deepen Naorem, Sanasam Ranbir Singh, Telem Joyson Singh, et al.*2026*
55. **[Learning Nested Named Entity Recognition from Flat Annotations](https://md.research.elamur.ai/free/en/papers/rozhkov-2026-learning-nested-named-entity-recognition/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Igor Rozhkov, Natalia V Loukachevitch*2026*
56. **[Merge and Conquer: Instructing Multilingual Models by Adding Target Language Weights](https://md.research.elamur.ai/free/en/papers/valero-2026-merge-conquer-instructing-multilingual-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Eneko Valero, Maria Ribalta i Albado, Oscar Sainz, et al.*2026*
57. **[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*
58. **[NASIMLab at SemEval-2026 Task 9: A Comparative Analysis of Fine-Tuned Small Language Models vs. Generative Large Language Models for Multilingual Polarization Type Detection](https://md.research.elamur.ai/free/en/papers/sabhahit-2026-nasimlab-semeval-2026-task-9/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Neel Sabhahit, Sanjeevan Selvaganapathy, Mehwish Nasim*2026*
59. **[NorBERTo: A ModernBERT Model Trained for Portuguese with 331 Billion Tokens Corpus](https://md.research.elamur.ai/free/en/papers/silva-2026-norberto-modernbert-model-trained-portuguese/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Enzo S. N. Silva, Pablo B. Costa, Raphael C. Vlasman, et al.*2026*
60. **[Parallel Universes, Parallel Languages: A Comprehensive Study on LLM-based Multilingual Counterfactual Example Generation](https://md.research.elamur.ai/free/en/papers/wang-2026-parallel-universes-parallel-languages-comprehensive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qianli Wang, Van Bach Nguyen, Yihong Liu, et al.*2026*
61. **[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*
62. **[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*
63. [**Reading the News: Adapting Large Language Models to Swedish Journalism Through Continued Pre-Training arXiv:2608.30609**Lukas Borggren, Jenny Kunz, Marco Kuhlmann*2026*](https://md.research.elamur.ai/free/en/papers/borggren-2026-reading-news-adapting-large-language/)
64. **[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*
65. **[Russian Generative Spelling, Punctuation and Capitalization Correction](https://md.research.elamur.ai/free/en/papers/martynov-2026-russian-generative-spelling-punctuation-capitalization/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Nikita Martynov, Danil Astafurov, Ulyana Isaeva, et al.*2026*
66. **[SiniticMTError: A Machine Translation Dataset with Error Annotations for Sinitic Languages](https://md.research.elamur.ai/free/en/papers/liu-2026-siniticmterror-machine-translation-dataset-error/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Hannah Liu, Junghyun Min, Annie En-Shiun Lee, et al.*2026*
67. **[TryggLLM: A Benchmark for Evaluating LLM Safety in Norwegian](https://md.research.elamur.ai/free/en/papers/touileb-2026-tryggllm-benchmark-evaluating-llm-safety/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Samia Touileb, Truls Pedersen, Isabell Stinessen Haugen*2026*
68. **[What does Surprisal have to do with Information Status?](https://md.research.elamur.ai/free/en/papers/dyer-2026-what-does-surprisal-have-do/) [Workshop on Research in Computational Linguistic Typology and Multilingual NLP](https://md.research.elamur.ai/free/en/venues/sigtyp/)**Andrew Thomas Dyer*2026*
69. [**Assessing the Agreement Competence of Large Language Models**Alba Táboas García, Leo Wanner*2025*](https://md.research.elamur.ai/free/en/papers/garcia-2025-assessing-agreement-competence-large-language/)

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

- [← back to](https://md.research.elamur.ai/free/en/authors/vladislav-mikhailov/) — Vladislav Mikhailov