---
title: "Who cites Matthias Gallé — 339 papers of our library"
description: "339 papers of the Elamur Research library cite the works of Matthias Gallé, found in their bibliographies; the most cited first."
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---
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# 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](https://md.research.elamur.ai/free/en/authors/matthias-galle/)

1. **[A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,286 citations*
2. [**AdapterFusion: Non-Destructive Task Composition for Transfer Learning arXiv:2005.00247 · Proceedings of EACL 2021**Jonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé, et al.*2020 · 950 citations*](https://md.research.elamur.ai/free/en/papers/pfeiffer-2020-adapterfusion-non-destructive-task-composition/)
3. [**BloombergGPT: A Large Language Model for Finance arXiv:2303.17564**Shijie Wu, Ozan Irsoy, Steven Lu, et al.*2023 · 612 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-bloomberggpt-large-language-model-finance/)
4. [**Kimi k1.5: Scaling Reinforcement Learning with LLMs arXiv:2501.12599**Kimi Team, Angang Du, Bofei Gao, et al.*2025 · 413 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k1-5-scaling-reinforcement/)
5. [**Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning arXiv:2503.09516**Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.*2025 · 303 citations*](https://md.research.elamur.ai/free/en/papers/jin-2025-search-r1-training-llms-reason/)
6. [**Understanding R1-Zero-Like Training: A Critical Perspective arXiv:2503.20783**Zichen Liu, Changyu Chen, Wenjun Li, et al.*2025 · 266 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-understanding-r1-zero-like-training/)
7. [**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/)
8. **[Language Model Tokenizers Introduce Unfairness Between Languages](https://md.research.elamur.ai/free/en/papers/petrov-2023-language-model-tokenizers-introduce-unfairness/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**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 paper**Yang Yue, Zhiqi Chen, Rui Lu, et al.*2025 · 196 citations*](https://md.research.elamur.ai/free/en/papers/yue-2025-reinforcement-learning-really-incentivize-reasoning/)
10. [**Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier arXiv:2412.04261**John Dang, Shivalika Singh, Daniel D'souza, et al.*2024 · 180 citations*](https://md.research.elamur.ai/free/en/papers/dang-2024-aya-expanse-combining-research-breakthroughs/)
11. **[Lifting the Curse of Multilinguality by Pre-training Modular Transformers](https://md.research.elamur.ai/free/en/papers/pfeiffer-2022-lifting-curse-multilinguality-pre-training/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jonas Pfeiffer, Naman Goyal, Xi Victoria Lin, et al.*2022 · 172 citations*
12. **[Sustainable Modular Debiasing of Language Models](https://md.research.elamur.ai/free/en/papers/lauscher-2021-sustainable-modular-debiasing-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Anne Lauscher, Tobias Lueken, Goran Glavaš*2021 · 165 citations*
13. **[Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models](https://md.research.elamur.ai/free/en/papers/ahia-2023-do-all-languages-cost-same/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.*2023 · 164 citations*
14. [**Training Language Models to Self-Correct via Reinforcement Learning arXiv:2409.12917**Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.*2024 · 151 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2024-training-language-models-self-correct/)
15. [**Process Reinforcement through Implicit Rewards arXiv:2502.01456**Ganqu Cui, Lifan Yuan, Zefan Wang, et al.*2025 · 147 citations*](https://md.research.elamur.ai/free/en/papers/cui-2025-process-reinforcement-through-implicit-rewards/)
16. [**Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs arXiv:2503.01307**Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, et al.*2025 · 110 citations*](https://md.research.elamur.ai/free/en/papers/gandhi-2025-cognitive-behaviors-that-enable-self/)
17. [**Benchmarking Machine Translation with Cultural Awareness arXiv:2305.14328**Binwei Yao, Ming Jiang, Tara Bobinac, et al.*2023 · 109 citations*](https://md.research.elamur.ai/free/en/papers/yao-2023-benchmarking-machine-translation-cultural-awareness/)
18. **[Learning Language Specific Sub-network for Multilingual Machine Translation](https://md.research.elamur.ai/free/en/papers/lin-2021-learning-language-specific-sub-network/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zehui Lin, Liwei Wu, Mingxuan Wang, et al.*2021 · 103 citations*
19. **[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 · 102 citations*
20. **[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 · 101 citations*
21. [**FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every Language arXiv:2506.20920**Guilherme Penedo, Hynek Kydliček, Vinko Sabolčec, et al.*2025 · 97 citations*](https://md.research.elamur.ai/free/en/papers/penedo-2025-fineweb2-one-pipeline-scale-them/)
22. [**UniMorph 4.0: Universal Morphology**Khuyagbaatar Batsuren, Omer Goldman, Salam Khalifa*2022 · 82 citations*](https://md.research.elamur.ai/free/en/papers/batsuren-2022-unimorph-4/)
23. [**Llama-Nemotron: Efficient Reasoning Models arXiv:2505.00949**Akhiad Bercovich, Itay Levy, Izik Golan, et al.*2025 · 75 citations*](https://md.research.elamur.ai/free/en/papers/bercovich-2025-llama-nemotron-efficient-reasoning-models/)
24. [**The SIGMORPHON 2022 Shared Task on Morpheme Segmentation**Khuyagbaatar Batsuren, Gabor Bella, Aryaman Arora*2022 · 71 citations*](https://md.research.elamur.ai/free/en/papers/batsuren-2022-morpheme-segmentation/)
25. [**Seed-TTS: A Family of High-Quality Versatile Speech Generation Models arXiv:2406.02430**Philip Anastassiou, Jiawei Chen, Jitong Chen, et al.*2024 · 69 citations*](https://md.research.elamur.ai/free/en/papers/anastassiou-2024-seed-tts-family-high/)
26. **[Tokenization Is More Than Compression](https://md.research.elamur.ai/free/en/papers/schmidt-2024-tokenization-is-more-than-compression/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Craig W Schmidt, Varshini Reddy, Haoran Zhang, et al.*2024 · 66 citations*
27. **[Fine-Grained Reward Optimization for Machine Translation using Error Severity Mappings](https://md.research.elamur.ai/free/en/papers/ramos-2026-fine-grained-reward-optimization-machine/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/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 Benchmarks**Go Inoue, Bashar Alhafni, Nizar Habash, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/inoue-2026-do-diacritics-matter-evaluating-impact/)
29. [**Morphemes Without Borders: Evaluating Root-Pattern Morphology in Arabic Tokenizers and LLMs arXiv:2603.15773**Yara Alakeel, Chatrine Qwaider, Hanan Aldarmaki, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alakeel-2026-morphemes-borders-evaluating-root-pattern/)
30. [**Morphemes without Borders: Evaluating Root–Pattern Morphology in Arabic Tokenizers and LLMs**Yara Yousif Alakeel, Chatrine Qwaider, Hanan Aldarmaki, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alakeel-2026-morphemes-without-borders-evaluating-root/)
31. **[Bringing Mapudungun into the Modern MT Ecosystem: Morphology-Aware Tokenization for NLLB-200 Fine-Tuning](https://md.research.elamur.ai/free/en/papers/thompson-2026-bringing-mapudungun-into-modern-mt/) [Workshop on NLP for Indigenous Languages of the Americas (AmericasNLP)](https://md.research.elamur.ai/free/en/venues/americasnlp/)**Isaac Thompson, Brandon Rogers, Eric Ringger*2026*
32. [**DeformAr: Rethinking NER Evaluation through Component Analysis and Visual Analytics arXiv:2512.00938**Ahmed Mustafa Younes*2025*](https://md.research.elamur.ai/free/en/papers/younes-2025-deformar-rethinking-ner-evaluation-through/)

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

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