🧑‍🔬 Who cites Matthias Gallé

339 citations of their works from 339 papers of our library (of the 141,840 whose bibliographies we read) · 32 with a page here, the most cited first · ← Matthias Gallé

1. A Comprehensive Overview of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyHumza Naveed, Asad Ullah Khan, Shi Qiu, et al.2023 · 1,286 citations
2. AdapterFusion: Non-Destructive Task Composition for Transfer LearningarXiv:2005.00247 · Proceedings of EACL 2021Jonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé, et al.2020 · 950 citations
3. BloombergGPT: A Large Language Model for FinancearXiv:2303.17564Shijie Wu, Ozan Irsoy, Steven Lu, et al.2023 · 612 citations
4. Kimi k1.5: Scaling Reinforcement Learning with LLMsarXiv:2501.12599Kimi Team, Angang Du, Bofei Gao, et al.2025 · 413 citations
5. Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement LearningarXiv:2503.09516Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.2025 · 303 citations
6. Understanding R1-Zero-Like Training: A Critical PerspectivearXiv:2503.20783Zichen Liu, Changyu Chen, Wenjun Li, et al.2025 · 266 citations
7. mGPT: Few-Shot Learners Go MultilingualarXiv:2204.07580Oleh Shliazhko, Alena Fenogenova, Maria Tikhonova, et al.2022 · 203 citations
8. Language Model Tokenizers Introduce Unfairness Between LanguagesConference on Neural Information Processing Systems (NeurIPS)Aleksandar Petrov, Emanuele La Malfa, Philip H. S. Torr, et al.2023 · 197 citations
9. Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?arXiv:2504.13837 · NeurIPS 2025 Oral; ICML 2025 AI4MATH workshop best paperYang Yue, Zhiqi Chen, Rui Lu, et al.2025 · 196 citations
10. Aya Expanse: Combining Research Breakthroughs for a New Multilingual FrontierarXiv:2412.04261John Dang, Shivalika Singh, Daniel D'souza, et al.2024 · 180 citations
11. Lifting the Curse of Multilinguality by Pre-training Modular TransformersConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Jonas Pfeiffer, Naman Goyal, Xi Victoria Lin, et al.2022 · 172 citations
12. Sustainable Modular Debiasing of Language ModelsFindings of the Association for Computational LinguisticsAnne Lauscher, Tobias Lueken, Goran Glavaš2021 · 165 citations
13. Do All Languages Cost the Same? Tokenization in the Era of Commercial Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.2023 · 164 citations
14. Training Language Models to Self-Correct via Reinforcement LearningarXiv:2409.12917Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.2024 · 151 citations
15. Process Reinforcement through Implicit RewardsarXiv:2502.01456Ganqu Cui, Lifan Yuan, Zefan Wang, et al.2025 · 147 citations
16. Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRsarXiv:2503.01307Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, et al.2025 · 110 citations
17. Benchmarking Machine Translation with Cultural AwarenessarXiv:2305.14328Binwei Yao, Ming Jiang, Tara Bobinac, et al.2023 · 109 citations
18. Learning Language Specific Sub-network for Multilingual Machine TranslationAnnual Meeting of the Association for Computational Linguistics (ACL)Zehui Lin, Liwei Wu, Mingxuan Wang, et al.2021 · 103 citations
19. Tokenizer Choice For LLM Training: Negligible or Crucial?Findings of the Association for Computational LinguisticsMehdi Ali, Michael Fromm, Klaudia Thellmann, et al.2024 · 102 citations
20. BLOOM+1: Adding Language Support to BLOOM for Zero-Shot PromptingAnnual Meeting of the Association for Computational Linguistics (ACL)Zheng Xin Yong, Hailey Schoelkopf, Niklas Muennighoff, et al.2023 · 101 citations
21. FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every LanguagearXiv:2506.20920Guilherme Penedo, Hynek Kydliček, Vinko Sabolčec, et al.2025 · 97 citations
22. UniMorph 4.0: Universal MorphologyKhuyagbaatar Batsuren, Omer Goldman, Salam Khalifa2022 · 82 citations
23. Llama-Nemotron: Efficient Reasoning ModelsarXiv:2505.00949Akhiad Bercovich, Itay Levy, Izik Golan, et al.2025 · 75 citations
24. The SIGMORPHON 2022 Shared Task on Morpheme SegmentationKhuyagbaatar Batsuren, Gabor Bella, Aryaman Arora2022 · 71 citations
25. Seed-TTS: A Family of High-Quality Versatile Speech Generation ModelsarXiv:2406.02430Philip Anastassiou, Jiawei Chen, Jitong Chen, et al.2024 · 69 citations
26. Tokenization Is More Than CompressionConference on Empirical Methods in Natural Language Processing (EMNLP)Craig W Schmidt, Varshini Reddy, Haoran Zhang, et al.2024 · 66 citations
27. Fine-Grained Reward Optimization for Machine Translation using Error Severity MappingsTransactions of the Association for Computational Linguistics (TACL)Miguel Moura Ramos, Tomás Almeida, Daniel Vareta, et al.2026 · 7 citations
28. Do Diacritics Matter? Evaluating the Impact of Arabic Diacritics on Tokenization and LLM BenchmarksGo Inoue, Bashar Alhafni, Nizar Habash, et al.2026 · 3 citations
29. Morphemes Without Borders: Evaluating Root-Pattern Morphology in Arabic Tokenizers and LLMsarXiv:2603.15773Yara Alakeel, Chatrine Qwaider, Hanan Aldarmaki, et al.2026 · 1 citation
30. Morphemes without Borders: Evaluating Root–Pattern Morphology in Arabic Tokenizers and LLMsYara Yousif Alakeel, Chatrine Qwaider, Hanan Aldarmaki, et al.2026 · 1 citation
31. Bringing Mapudungun into the Modern MT Ecosystem: Morphology-Aware Tokenization for NLLB-200 Fine-TuningWorkshop on NLP for Indigenous Languages of the Americas (AmericasNLP)Isaac Thompson, Brandon Rogers, Eric Ringger2026
32. DeformAr: Rethinking NER Evaluation through Component Analysis and Visual AnalyticsarXiv:2512.00938Ahmed Mustafa Younes2025

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