🧑‍🔬 Who cites Jeffrey Li

223 citations of their works from 214 papers of our library (of the 149,439 whose bibliographies we read) · 53 with a page here, the most cited first · ← Jeffrey Li

1. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
2. Kimi k1.5: Scaling Reinforcement Learning with LLMsarXiv:2501.12599Kimi Team, Angang Du, Bofei Gao, et al.2025 · 431 citations
3. RedPajama: an Open Dataset for Training Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Maurice Weber, Daniel Fu, Quentin Anthony, et al.2024 · 260 citations
4. DataComp-LM: In search of the next generation of training sets for language modelsConference on Neural Information Processing Systems (NeurIPS)Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.2024 · 191 citations
5. SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language ModelarXiv:2502.02737Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.2025 · 181 citations
6. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
7. Fanar: An Arabic-Centric Multimodal Generative AI PlatformarXiv:2501.13944Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.2025 · 127 citations
8. OpenThoughts: Data Recipes for Reasoning ModelsarXiv:2506.04178Etash Guha, Ryan Marten, Sedrick Keh, et al.2025 · 122 citations
9. 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 · 99 citations
10. GLM-5: from Vibe Coding to Agentic EngineeringarXiv:2602.15763Aohan Zeng, Xin Lv, Zhenyu Hou, et al.2026 · 95 citations
11. How to Train Long-Context Language Models (Effectively)Annual Meeting of the Association for Computational Linguistics (ACL)Tianyu Gao, Alexander Wettig, Howard Yen, et al.2025 · 89 citations
12. Small Language Models: Survey, Measurements, and InsightsarXiv:2409.15790Zhenyan Lu, Xiang Li, Dongqi Cai, et al.2024 · 88 citations
13. Apertus: Democratizing Open and Compliant LLMs for Global Language EnvironmentsAnnual Meeting of the Association for Computational Linguistics (ACL)Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.2026 · 68 citations
14. Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining DatasetAnnual Meeting of the Association for Computational Linguistics (ACL)Dan Su, Kezhi Kong, Ying Lin, et al.2025 · 65 citations
15. mmBERT: A Modern Multilingual Encoder with Annealed Language LearningarXiv:2509.06888Marc Marone, Orion Weller, William Fleshman, et al.2025 · 59 citations
16. Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling LawsarXiv:2401.00448Nikhil Sardana, Jacob Portes, Sasha Doubov, et al.2024 · 57 citations
17. RegMix: Data Mixture as Regression for Language Model Pre-trainingarXiv:2407.01492Qian Liu, Xiaosen Zheng, Niklas Muennighoff, et al.2024 · 57 citations
18. Hymba: A Hybrid-head Architecture for Small Language ModelsarXiv:2411.13676Xin Dong, Yonggan Fu, Shizhe Diao, et al.2024 · 50 citations
19. Scaling Laws with Vocabulary: Larger Models Deserve Larger VocabulariesarXiv:2407.13623Chaofan Tao, Qian Liu, Longxu Dou, et al.2024 · 46 citations
20. olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language ModelsarXiv:2502.18443Jake Poznanski, Aman Rangapur, Jon Borchardt, et al.2025 · 44 citations
21. Paloma: A Benchmark for Evaluating Language Model FitConference on Neural Information Processing Systems (NeurIPS)Ian Magnusson, Akshita Bhagia, Valentin Hofmann, et al.2023 · 42 citations
22. Observational Scaling Laws and the Predictability of Language Model PerformancearXiv:2405.10938Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto2024 · 40 citations
23. Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer ModelsarXiv:2504.03624NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.2025 · 38 citations
24. Scaling Laws and Compute-Optimal Training Beyond Fixed Training DurationsConference on Neural Information Processing Systems (NeurIPS)Alexander Hägele, Elie Bakouch, Atli Kosson, et al.2024 · 31 citations
25. Towards Effective and Efficient Continual Pre-training of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jie Chen, Zhipeng Chen, Jiapeng Wang, et al.2025 · 29 citations
26. Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic ReasoningarXiv:2512.20848NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.2025 · 27 citations
27. Distillation Scaling LawsarXiv:2502.08606Dan Busbridge, Amitis Shidani, Floris Weers, et al.2025 · 26 citations
28. RWKV-7 "Goose" with Expressive Dynamic State EvolutionarXiv:2503.14456Bo Peng, Ruichong Zhang, Daniel Goldstein, et al.2025 · 23 citations
29. MiniCPM4: Ultra-Efficient LLMs on End DevicesarXiv:2506.07900MiniCPM Team, Chaojun Xiao, Yuxuan Li, et al.2025 · 22 citations
30. Scaling Latent Reasoning via Looped Language ModelsarXiv:2510.25741Rui-Jie Zhu, Zixuan Wang, Kai Hua, et al.2025 · 22 citations
31. Resolving Discrepancies in Compute-Optimal Scaling of Language ModelsConference on Neural Information Processing Systems (NeurIPS)Tomer Porian, Mitchell Wortsman, Jenia Jitsev, et al.2024 · 19 citations
32. Dataset Decomposition: Faster LLM Training with Variable Sequence Length CurriculumConference on Neural Information Processing Systems (NeurIPS)Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, et al.2024 · 16 citations
33. Rethinking Reflection in Pre-TrainingarXiv:2504.04022Essential AI: Darsh J Shah, Peter Rushton, Somanshu Singla, et al.2025 · 15 citations
34. Maximize Your Data's Potential: Enhancing LLM Accuracy with Two-Phase PretrainingarXiv:2412.15285Steven Feng, Shrimai Prabhumoye, Kezhi Kong, et al.2024 · 12 citations
35. MiniPLM: Knowledge Distillation for Pre-Training Language ModelsarXiv:2410.17215Yuxian Gu, Hao Zhou, Fandong Meng, et al.2024 · 12 citations
36. Bilingual Adaptation of Monolingual Foundation ModelsarXiv:2407.12869Gurpreet Gosal, Yishi Xu, Gokul Ramakrishnan, et al.2024 · 7 citations
37. Arabic Stable LM: Adapting Stable LM 2 1.6B to ArabicarXiv:2412.04277Zaid Alyafeai, Michael Pieler, Hannah Teufel, et al.2024 · 6 citations
38. Aleph-Alpha-GermanWeb: Improving German-language LLM pre-training with model-based data curation and synthetic data generationConference of the European Chapter of the Association for Computational Linguistics (EACL)Thomas F Burns, Letitia Parcalabescu, Stephan Waeldchen, et al.2026 · 4 citations
39. Large Language Models for Mental Health: A Multilingual EvaluationWorkshop on Language Models for Low-Resource LanguagesNishat Raihan, Sadiya Sayara Chowdhury Puspo, Ana-Maria Bucur, et al.2026 · 4 citations
40. QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented GenerationFindings of the Association for Computational LinguisticsDehai Min, Kailin Zhang, Tongtong Wu, et al.2026 · 2 citations
41. The olmOCR Project: Building Fully Open OCR using VLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Jake Poznanski, Kyle Lo, Luca Soldaini2026 · 2 citations
42. Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-trainingAnnual Meeting of the Association for Computational Linguistics (ACL)Kailai Yang, Xiao Liu, Lei Ji, et al.2026 · 1 citation
43. KletterMix: Climbing Toward High-Quality German Pretraining Data - The Full ReportarXiv:2606.03773Maurice Kraus, Ruben Harle, Sebastian Sztwiertnia, et al.2026 · 1 citation
44. Biomed-Enriched: Data-Efficient Biomedical Pretraining via Paragraph-Level AnnotationFindings of the Association for Computational LinguisticsRian Touchent, Nathan Godey, Éric Villemonte de la Clergerie2026
45. Dialectal Filtering: Synthesizing Kurdish Corpora for Low-Resource Varieties by Utilizing “Noise” in Large Textual DataLanguage Resources and Evaluation Conference (LREC)Christian Schuler, Raman Ahmad, Ānrán Wáng, et al.2026
46. Merge and Conquer: Instructing Multilingual Models by Adding Target Language WeightsLanguage Resources and Evaluation Conference (LREC)Eneko Valero, Maria Ribalta i Albado, Oscar Sainz, et al.2026
47. Probing the Dynamics of Syntactic Ability Acquisition Throughout LLM PretrainingHiroshi Matsuda, Masayuki Asahara2026
48. Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New PerspectivesFindings of the Association for Computational LinguisticsYajiao Liu, Congliang Chen, Junchi Yang, et al.2026
49. Rewriting History: A Recipe for Interventional Analyses to Study Data Effects on Model BehaviorTransactions of the Association for Computational Linguistics (TACL)Rahul Nadkarni, Yanai Elazar, Hila Gonen, et al.2026
50. SciPedia: Unlocking the Value of Scientific Data for Pre-trainingAnnual Meeting of the Association for Computational Linguistics (ACL)Yiwei Qin, Zhen Huang, Tiantian Mi, et al.2026
51. SELECting over Tokens: Curating Pre-training Data at Scale via Token ClassificationAnnual Meeting of the Association for Computational Linguistics (ACL)Xin Tong, Weidong Zhang, Jiaang Li, et al.2026
52. Systematic Evaluation of the Quality of Synthetic Clinical Notes Rephrased by LLMs at Million-Note ScaleBioNLPJinghui Liu, Sarvesh Soni, Anthony Nguyen2026
53. UniGeM: Unifying Data Selection and Mixing via Geometric Exploration and MiningFindings of the Association for Computational LinguisticsChanghao Wang, Yunfeiyu, Xinhao Yao, et al.2026

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