---
title: "Who cites Celine Hudelot — 215 papers of our library"
description: "215 papers of the Elamur Research library cite the works of Celine Hudelot, found in their bibliographies; the most cited first."
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---
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# Who cites Celine Hudelot

220 citations of their works from 215 papers of our library (of the 149,439 whose bibliographies we read) · 52 with a page here, the most cited first · [← Celine Hudelot](https://md.research.elamur.ai/free/en/authors/celine-hudelot/)

1. [**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/)
2. [**Tower: An Open Multilingual Large Language Model for Translation-Related Tasks arXiv:2402.17733**Duarte M. Alves, Jose Pombal, Nuno M. Guerreiro, et al.*2024 · 227 citations*](https://md.research.elamur.ai/free/en/papers/alves-2024-tower-open-multilingual-large-language/)
3. [**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 · 99 citations*](https://md.research.elamur.ai/free/en/papers/penedo-2025-fineweb2-one-pipeline-scale-them/)
4. [**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/)
5. **[ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning Agents](https://md.research.elamur.ai/free/en/papers/wang-2025-vidorag-visual-document-retrieval-augmented/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qiuchen Wang, Ruixue Ding, Zehui Chen, et al.*2025 · 39 citations*
6. **[Dual-Space Knowledge Distillation for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-dual-space-knowledge-distillation-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Songming Zhang, Xue Zhang, Zengkui Sun, et al.*2024 · 39 citations*
7. [**A Survey of Small Language Models arXiv:2410.20011**Chien Van Nguyen, Xuan Shen, Ryan Aponte, et al.*2024 · 31 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2024-survey-small-language-models/)
8. [**Beyond English-Centric LLMs: What Language Do Multilingual Language Models Think in? arXiv:2408.10811**Chengzhi Zhong, Fei Cheng, Qianying Liu, et al.*2024 · 24 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-english-centric-llms-language-multilingual/)
9. **[VRAG-RL: Empower Vision-Perception-Based RAG for Visually Rich Information Understanding via Iterative Reasoning with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2025-vrag-rl-empower-vision-perception/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Qiuchen Wang, Ruixue Ding, Yu Zeng, et al.*2025 · 23 citations*
10. **[REAL-MM-RAG: A Real-World Multi-Modal Retrieval Benchmark](https://md.research.elamur.ai/free/en/papers/wasserman-2025-real-mm-rag-real-world/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Navve Wasserman, Roi Pony, Oshri Naparstek, et al.*2025 · 22 citations*
11. **[VISA: Retrieval Augmented Generation with Visual Source Attribution](https://md.research.elamur.ai/free/en/papers/ma-2025-visa-retrieval-augmented-generation-visual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xueguang Ma, Shengyao Zhuang, Bevan Koopman, et al.*2025 · 22 citations*
12. **[M-LongDoc: A Benchmark For Multimodal Super-Long Document Understanding And A Retrieval-Aware Tuning Framework](https://md.research.elamur.ai/free/en/papers/chia-2025-m-longdoc-benchmark-multimodal-super/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yew Ken Chia, Liying Cheng, Hou Pong Chan, et al.*2025 · 21 citations*
13. **[SimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative Refinement](https://md.research.elamur.ai/free/en/papers/jain-2025-simpledoc-multi-modal-document-understanding/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chelsi Jain, Yiran Wu, Yifan Zeng, et al.*2025 · 16 citations*
14. **[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*
15. [**MiniPLM: Knowledge Distillation for Pre-Training Language Models arXiv:2410.17215**Yuxian Gu, Hao Zhou, Fandong Meng, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-miniplm-knowledge-distillation-pre-training/)
16. **[EMO: Embedding Model Distillation via Intra-Model Relation and Optimal Transport Alignments](https://md.research.elamur.ai/free/en/papers/truong-2025-emo-embedding-model-distillation-intra/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Minh-Phuc Truong, Hai An Vu, Tu Vu, et al.*2025 · 10 citations*
17. [**Why do small language models underperform? Studying Language Model Saturation via the Softmax Bottleneck arXiv:2404.07647**Nathan Godey, Eric de la Clergerie, Benoit Sagot*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/godey-2024-why-small-language-models-underperform/)
18. [**CTPD: Cross Tokenizer Preference Distillation arXiv:2601.11865**Truong Nguyen, Phi Van Dat, Ngan Nguyen, et al.*2026 · 8 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2026-ctpd-cross-tokenizer-preference-distillation/)
19. **[New Encoders for German Trained from Scratch: Comparing ModernGBERT with Converted LLM2Vec Models](https://md.research.elamur.ai/free/en/papers/wunderle-2026-new-encoders-german-trained-scratch/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Julia Wunderle, Anton Ehrmanntraut, Jan Pfister, et al.*2026 · 7 citations*
20. **[ViDoRe V3: A Comprehensive Evaluation of Retrieval Augmented Generation in Complex Real-World Scenarios](https://md.research.elamur.ai/free/en/papers/loison-2026-vidore-v3-comprehensive-evaluation-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**António Loison, Quentin Macé, Antoine Edy, et al.*2026 · 7 citations*
21. **[Doc-React: Multi-page Heterogeneous Document Question-answering](https://md.research.elamur.ai/free/en/papers/wu-2025-doc-react-multi-page-heterogeneous/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junda Wu, Yu Xia, Tong Yu, et al.*2025 · 6 citations*
22. **[Sparse Logit Sampling: Accelerating Knowledge Distillation in LLMs](https://md.research.elamur.ai/free/en/papers/anshumann-2025-sparse-logit-sampling-accelerating-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Anshumann, Mohd Abbas Zaidi, Akhil Kedia, et al.*2025 · 6 citations*
23. **[Cross-Tokenizer LLM Distillation through a Byte-Level Interface](https://md.research.elamur.ai/free/en/papers/singh-2026-cross-tokenizer-llm-distillation-through/) [Workshop on Customizable NLP: Progress and Challenges in Customizing NLP for a Domain, Application, Group, or Individual](https://md.research.elamur.ai/free/en/venues/customnlp4u/)**Avyav Kumar Singh, Yen-Chen Wu, Alexandru Cioba, et al.*2026 · 5 citations*
24. **[LAD-RAG: Layout-aware Dynamic RAG for Visually-Rich Document Understanding](https://md.research.elamur.ai/free/en/papers/sourati-2026-lad-rag-layout-aware-dynamic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhivar Sourati, Zheng Wang, Marianne Menglin Liu, et al.*2026 · 4 citations*
25. **[DocLens: A Tool-Augmented Multi-Agent Framework for Long Visual Document Understanding](https://md.research.elamur.ai/free/en/papers/zhu-2026-doclens-tool-augmented-multi-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dawei Zhu, Rui Meng, Jiefeng Chen, et al.*2026 · 2 citations*
26. **[Sculpting the Vector Space: Towards Efficient Multi-Vector Visual Document Retrieval via Prune-then-Merge Framework](https://md.research.elamur.ai/free/en/papers/yan-2026-sculpting-vector-space-efficient-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Yan, Mingdong Ou, Yi Cao, et al.*2026 · 2 citations*
27. **[Transforming Causal LLM into MLM Encoder for Detecting Social Media Manipulation in Telegram](https://md.research.elamur.ai/free/en/papers/bazdyrev-2025-transforming-causal-llm-into-mlm/) [Ukrainian Natural Language Processing Workshop](https://md.research.elamur.ai/free/en/venues/unlp/)**Anton Bazdyrev, Ivan Bashtovyi, Ivan Havlytskyi, et al.*2025 · 2 citations*
28. **[Agentic Very Long Video Understanding](https://md.research.elamur.ai/free/en/papers/rege-2026-agentic-very-long-video-understanding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aniket Rege, Arka Sadhu, Yuliang Li, et al.*2026 · 1 citation*
29. **[CEFR-Cymraeg: A Dataset and Baseline Models for Language Proficiency Assessment in Welsh](https://md.research.elamur.ai/free/en/papers/waqar-2026-cefr-cymraeg-dataset-baseline-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Eeshan Waqar, Jonathan Davies, Dawn Knight, et al.*2026 · 1 citation*
30. **[Efficient Table Retrieval and Understanding with Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-efficient-table-retrieval-understanding-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuoyan Xu, Haoyang Fang, Boran Han, et al.*2026 · 1 citation*
31. **[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*
32. **[Knowledge Extraction on Semi-Structured Content: Does It Remain Relevant for Question Answering in the Era of LLMs?](https://md.research.elamur.ai/free/en/papers/sun-2026-knowledge-extraction-semi-structured-content/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Kai Sun, Yin Huang, Srishti Mehra, et al.*2026 · 1 citation*
33. **[SCAN: Semantic Document Layout Analysis for Textual and Visual Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/ueda-2026-scan-semantic-document-layout-analysis/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nobuhiro Ueda, Yuyang Dong, Krisztián Boros, et al.*2026 · 1 citation*
34. **[SindBERT, the Sailor: Charting the Seas of Turkish NLP](https://md.research.elamur.ai/free/en/papers/schmitt-2026-sindbert-sailor-charting-seas-turkish/) [Workshop Natural Language Processing for Turkic Languages](https://md.research.elamur.ai/free/en/venues/sigturk/)**Raphael Schmitt, Stefan Schweter*2026 · 1 citation*
35. **[UMUTeam at SemEval-2026 Task 10: Transformer Ensembles for Conspiratorial Span Extraction and Detection](https://md.research.elamur.ai/free/en/papers/navalon-2026-umuteam-semeval-2026-task-10/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Jorge Gómez-Navalón, Ronghao Pan, Tomás Bernal-Beltrán, et al.*2026 · 1 citation*
36. **[VisTW: Benchmarking Vision-Language Models for Taiwanese Mandarin in Taiwan](https://md.research.elamur.ai/free/en/papers/tam-2026-vistw-benchmarking-vision-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhi Rui Tam, Yung-Yu Shih, Yen-Wei Lee, et al.*2026 · 1 citation*
37. **[A multilingual hallucination benchmark](https://md.research.elamur.ai/free/en/papers/thoresen-2026-multilingual-hallucination-benchmark/) [Workshop on the Role of Resources in the Age of Large Language Models](https://md.research.elamur.ai/free/en/venues/resourceful/)**Freja Thoresen, Dan Saattrup Smart*2026*
38. **[Detecting Non-Membership in LLM Training Data via Rank Correlations](https://md.research.elamur.ai/free/en/papers/shetty-2026-detecting-non-membership-llm-training/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Pranav Shetty, Mirazul Haque, Zhiqiang Ma, et al.*2026*
39. **[Diagnosing Translated Benchmarks: An Automated Quality Assurance Study of the EU20 Benchmark Suite](https://md.research.elamur.ai/free/en/papers/thellmann-2026-diagnosing-translated-benchmarks-automated-quality/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Klaudia Thellmann, Bernhard Stadler, Michael Färber*2026*
40. **[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*
41. **[Evaluating Perspectival Biases in Cross-Modal Retrieval](https://md.research.elamur.ai/free/en/papers/saengsukhiran-2026-evaluating-perspectival-biases-cross-modal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Teerapol Saengsukhiran, Peerawat Chomphooyod, Narabodee Rodjananant, et al.*2026*
42. **[GATech at AbjadMed: Bidirectional Encoders vs. Causal Decoders: Insights from 82-Class Arabic Medical Classification](https://md.research.elamur.ai/free/en/papers/khamis-2026-gatech-abjadmed-bidirectional-encoders-vs/) [Workshop on NLP for Languages Using Arabic Script](https://md.research.elamur.ai/free/en/venues/abjadnlp/)**Ahmed Khamis*2026*
43. **[GePaDeSE: A New Resource for Clause-Level Aspect in German Parliamentary Debates](https://md.research.elamur.ai/free/en/papers/schlenker-2026-gepadese-new-resource-clause-level/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Julian Schlenker, Ines Rehbein, Lilly Brauner, et al.*2026*
44. **[HiKEY: Hierarchical Multimodal Retrieval for Open-Domain Document Question Answering](https://md.research.elamur.ai/free/en/papers/shin-2026-hikey-hierarchical-multimodal-retrieval-open/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joongmin Shin, Gyuho Shim, Jeongbae Park, et al.*2026*
45. [**Ideology Prediction of German Political Texts arXiv:2605.14352**Sinclair Schneider, Florian Steuber, Joao A. G. Schneider, et al.*2026*](https://md.research.elamur.ai/free/en/papers/schneider-2026-ideology-prediction-german-political-texts/)
46. [**LëtzCross: A Cross-Lingual Page-Level Benchmark for Multimodal Retrieval over Luxembourgish Documents arXiv:2608.21714**Omar El Bachyr, Fred Philippy, Laura Maria Bernardy, et al.*2026*](https://md.research.elamur.ai/free/en/papers/bachyr-2026-l-etzcross-cross-lingual-page/)
47. **[MDocRAG-RL: Empowering Multi-Modal Document RAG via Complex Visual Reasoning with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-mdocrag-rl-empowering-multi-modal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhongyu Wang*2026*
48. **[Quantifying the Impact of Translation Errors on Multilingual LLM Evaluation](https://md.research.elamur.ai/free/en/papers/thellmann-2026-quantifying-impact-translation-errors-multilingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Klaudia Thellmann, Bernhard Stadler, Michael Färber, et al.*2026*
49. [**Repetition over Diversity: High-Signal Data Filtering for Sample-Efficient German Language Modeling arXiv:2604.28075**Ansar Aynetdinov, Patrick Haller, Alan Akbik*2026*](https://md.research.elamur.ai/free/en/papers/aynetdinov-2026-repetition-over-diversity-high-signal/)
50. **[SwissGov-RSD: A Human-annotated, Cross-lingual Benchmark for Token-level Recognition of Semantic Differences Between Related Documents](https://md.research.elamur.ai/free/en/papers/wastl-2026-swissgov-rsd-human-annotated-cross/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michelle Wastl, Jannis Vamvas, Rico Sennrich*2026*
51. **[Take It All: Ensemble Retrieval for Multimodal Evidence Aggregation](https://md.research.elamur.ai/free/en/papers/upravitelev-2026-take-it-all-ensemble-retrieval/) [Fact Extraction and VERification Workshop (FEVER)](https://md.research.elamur.ai/free/en/venues/fever/)**Max Upravitelev, Veronika Solopova, Premtim Sahitaj, et al.*2026*
52. **[When Tables Go Crazy: Evaluating Multimodal Models on French Financial Documents](https://md.research.elamur.ai/free/en/papers/mouilleron-2026-when-tables-go-crazy-evaluating/) [Financial Narrative Processing Workshop](https://md.research.elamur.ai/free/en/venues/fnp/)**Virginie Mouilleron, Théo Lasnier, Anna Mosolova, et al.*2026*

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

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