---
title: "Who cites Mateusz Lango — 130 papers of our library"
description: "130 papers of the Elamur Research library cite the works of Mateusz Lango, found in their bibliographies; the most cited first."
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---
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# Who cites Mateusz Lango

130 citations of their works from 130 papers of our library (of the 149,439 whose bibliographies we read) · 28 with a page here, the most cited first · [← Mateusz Lango](https://md.research.elamur.ai/free/en/authors/mateusz-lango/)

1. [**LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks arXiv:2406.18403**Anna Bavaresco, Raffaella Bernardi, Leonardo Bertolazzi, et al.*2024 · 141 citations*](https://md.research.elamur.ai/free/en/papers/bavaresco-2024-llms-instead-human-judges-large/)
2. **[A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.*2024 · 105 citations*
3. **[MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks](https://md.research.elamur.ai/free/en/papers/ahuja-2024-megaverse-benchmarking-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sanchit Ahuja, Divyanshu Aggarwal, Varun Gumma, et al.*2024 · 74 citations*
4. [**Beyond Accuracy: Evaluating the Reasoning Behavior of Large Language Models — A Survey arXiv:2404.01869**Philipp Mondorf, Barbara Plank*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/mondorf-2024-accuracy-evaluating-reasoning-behavior-large/)
5. **[VariErr NLI: Separating Annotation Error from Human Label Variation](https://md.research.elamur.ai/free/en/papers/genzel-2024-varierr-nli-separating-annotation-error/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Leon Weber-Genzel, Siyao Peng, Marie-Catherine De Marneffe, et al.*2024 · 51 citations*
6. **[On Memorization of Large Language Models in Logical Reasoning](https://md.research.elamur.ai/free/en/papers/xie-2025-memorization-large-language-models-logical/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Chulin Xie, Yangsibo Huang, Chiyuan Zhang, et al.*2025 · 45 citations*
7. **[“Seeing the Big through the Small”: Can LLMs Approximate Human Judgment Distributions on NLI from a Few Explanations?](https://md.research.elamur.ai/free/en/papers/chen-2024-seeing-big-through-small-can/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Beiduo Chen, Xinpeng Wang, Siyao Peng, et al.*2024 · 18 citations*
8. **[DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph](https://md.research.elamur.ai/free/en/papers/zhang-2024-darg-dynamic-evaluation-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhehao Zhang, Jiaao Chen, Diyi Yang*2024 · 17 citations*
9. **[Towards Data Contamination Detection for Modern Large Language Models: Limitations, Inconsistencies, and Oracle Challenges](https://md.research.elamur.ai/free/en/papers/samuel-2025-data-contamination-detection-modern-large/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Vinay Samuel, Yue Zhou, Henry Peng Zou*2025 · 16 citations*
10. **[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*
11. **[A Survey on Efficient Large Language Model Training: From Data-centric Perspectives](https://md.research.elamur.ai/free/en/papers/luo-2025-survey-efficient-large-language-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyu Luo, Bohan Wu, Xiao Luo, et al.*2025 · 14 citations*
12. [**Speak & Improve Corpus 2025: an L2 English Speech Corpus for Language Assessment and Feedback arXiv:2412.11986**Kate Knill, Diane Nicholls, Mark J.F. Gales, et al.*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/knill-2024-speak-improve-corpus-2025-l2/)
13. **[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*
14. **[How Quantization Shapes Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/marcuzzi-2026-how-quantization-shapes-bias-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Federico Marcuzzi, Xuefei Ning, Roy Schwartz, et al.*2026 · 3 citations*
15. **[LLM-Powered Benchmark Factory: Reliable, Generic, and Efficient](https://md.research.elamur.ai/free/en/papers/yuan-2026-llm-powered-benchmark-factory-reliable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peiwen Yuan, Shaoxiong Feng, Yiwei Li, et al.*2026 · 3 citations*
16. **[Colloquial Singaporean English Style Transfer with Fine-Grained Explainable Control](https://md.research.elamur.ai/free/en/papers/liang-2025-colloquial-singaporean-english-style-transfer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinggui Liang, Dung Vo, Yap Hong Xian, et al.*2025 · 2 citations*
17. **[Are LLM Benchmarks Already Contaminated? A Systematic Review of Contamination Detection Methods](https://md.research.elamur.ai/free/en/papers/nourbakhsh-2026-are-llm-benchmarks-already-contaminated/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Erfan Nourbakhsh, Mohammad Sadegh Sirjani, Amir Mousavi, et al.*2026*
18. [**Can Large Language Models Reliably Correct Errors in Low-Resource ASR? A Contamination-Aware Case Study on West Frisian arXiv:2605.19711**Yun Hao, Reihaneh Amooie, Wietse de Vries, et al.*2026*](https://md.research.elamur.ai/free/en/papers/hao-2026-large-language-models-reliably-correct/)
19. **[CLARIN-PT-LDB: An Open LLM Leaderboard for Portuguese to assess Language, Culture and Civility](https://md.research.elamur.ai/free/en/papers/silva-2026-clarin-pt-ldb-open-llm/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**João Ricardo Silva, Luís Gomes, António Branco*2026*
20. **[HotelCheckSpan: A Benchmark Dataset for LLM Faithfulness](https://md.research.elamur.ai/free/en/papers/schmidtova-2026-hotelcheckspan-benchmark-dataset-llm-faithfulness/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Patricia Schmidtova, Ondrej Dusek, Saad Mahamood*2026*
21. **[LLM Multi-Agent Systems for Long Triple Set Data-to-Text Generation](https://md.research.elamur.ai/free/en/papers/osuji-2026-llm-multi-agent-systems-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chinonso Cynthia Osuji, Simon Mille, Mark Andrade, et al.*2026*
22. **[LLM-FK: Multi-Agent LLM Reasoning for Foreign Key Detection in Large-Scale Complex Databases](https://md.research.elamur.ai/free/en/papers/tang-2026-llm-fk-multi-agent-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zijian Tang, Ying Zhang, Sibo Cai, et al.*2026*
23. [**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/)
24. **[NLG Evaluation: Past, Present, Future](https://md.research.elamur.ai/free/en/papers/reiter-2026-nlg-evaluation-past-present-future/) [Symposium on Natural Language Generation Evaluations](https://md.research.elamur.ai/free/en/venues/retroeval/)**Ehud Reiter*2026*
25. [**Obscuring Data Contamination Through Translation: Evidence from Arabic Corpora arXiv:2601.14994**Chaymaa Abbas, Nour Shamaa, Mariette Awad*2026*](https://md.research.elamur.ai/free/en/papers/abbas-2026-obscuring-data-contamination-through-translation/)
26. **[OpenSubtitles2024: A Massively Parallel Dataset of Movie Subtitles for MT Development and Evaluation](https://md.research.elamur.ai/free/en/papers/tiedemann-2026-opensubtitles2024-massively-parallel-dataset-movie/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Joerg Tiedemann, Hengyu Luo*2026*
27. **[QFinZero: A Unified Financial Toolchain for LLM-Based Trading Agents](https://md.research.elamur.ai/free/en/papers/luo-2026-qfinzero-unified-financial-toolchain-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haochen Luo, Yifan LI, Ho Tin Ko, et al.*2026*
28. **[R.U.Psycho? A Framework for Robust Unified Psychometric Testing of Language Models](https://md.research.elamur.ai/free/en/papers/schelb-2026-r-u-psycho-framework-robust/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Julian Schelb, Orr Borin, David Garcia, et al.*2026*

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

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