--- title: "Who cites FineWeb2: One Pipeline to Scale — 97 citing papers" description: "97 papers of the Elamur Research library cite «FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every…" canonical: "https://research.elamur.ai/free/en/papers/penedo-2025-fineweb2-one-pipeline-scale-them/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/penedo-2025-fineweb2-one-pipeline-scale-them/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [FineWeb2: One Pipeline to Scale Them All…](https://md.research.elamur.ai/free/en/papers/penedo-2025-fineweb2-one-pipeline-scale-them/) / cited by # Who cites «FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every Language» 97 papers of our library cite it (of the 141,840 whose bibliographies we read) · 14 with a page here, the most cited first · [← back to «FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every Language»](https://md.research.elamur.ai/free/en/papers/penedo-2025-fineweb2-one-pipeline-scale-them/) 1. [**GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models arXiv:2508.06471**Aohan Zeng, Xin Lv, Qinkai Zheng, et al.*2025 · 157 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-4-glm-4-5-agentic/) 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 · 67 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. [**Dicta-LM 3.0: Advancing The Frontier of Hebrew Sovereign LLMs**Shaltiel Shmidman, Avi Shmidman, Amir DN Cohen, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2026-dicta-lm-3-0-advancing/) 5. **[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* 6. **[Mining Naturally Romanized Seed Corpora without Romanizations](https://md.research.elamur.ai/free/en/papers/benton-2026-mining-naturally-romanized-seed-corpora/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Adrian Benton, Alexander Gutkin, Christo Kirov, et al.*2026 · 1 citation* 7. **[Child-directed speech facilitates production, not comprehension, in BabyLMs](https://md.research.elamur.ai/free/en/papers/bunzeck-2026-child-directed-speech-facilitates-production/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Bastian Bunzeck, Sina Zarrieß*2026* 8. **[Crowdsourcing Piedmontese to Test LLMs on Non-Standard Orthography](https://md.research.elamur.ai/free/en/papers/vico-2026-crowdsourcing-piedmontese-test-llms-non/) [Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial)](https://md.research.elamur.ai/free/en/venues/vardial/)**Gianluca Vico, Jindřich Libovický*2026* 9. **[Dialectal Filtering: Synthesizing Kurdish Corpora for Low-Resource Varieties by Utilizing “Noise” in Large Textual Data](https://md.research.elamur.ai/free/en/papers/schuler-2026-dialectal-filtering-synthesizing-kurdish-corpora/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Christian Schuler, Raman Ahmad, Ānrán Wáng, et al.*2026* 10. **[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* 11. **[ForumOccitania: A Corpus of User-Generated Content for Multiple Occitan Varieties](https://md.research.elamur.ai/free/en/papers/nedey-2026-forumoccitania-corpus-user-generated-content/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Oriane Nédey, Juliette Janès, Rachel Bawden, et al.*2026* 12. **[GPT-NL Public Corpus: A Permissively Licensed, Dutch-First Dataset for LLM Pre-training](https://md.research.elamur.ai/free/en/papers/oort-2026-gpt-nl-public-corpus-permissively/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Jesse J. Van Oort, Frank Brinkkemper, Erik de Graaf, et al.*2026* 13. **[Nepali Lemmatization with Multilingual Transformers: Intrinsic and Extrinsic Evaluation in a Low-Resource Setting](https://md.research.elamur.ai/free/en/papers/regmi-2026-nepali-lemmatization-multilingual-transformers-intrinsic/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Sunil Regmi, Sundeep Dawadi, Bal Krishna Bal*2026* 14. [**Wasm: A Pipeline for Constructing Structured Arabic Interleaved Multimodal Corpora arXiv:2511.07080**Khalil Hennara; Ahmad Bastati; Muhammad Hreden; Mohamed Motasim Hamed; Zeina Aldallal; Sara Chrouf;, Safwan AlModhayan*2025*](https://md.research.elamur.ai/free/en/papers/hennara-2025-wasm-pipeline-constructing-structured-arabic/) 83 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/penedo-2025-fineweb2-one-pipeline-scale-them/) — FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every Language