🔗 Who cites «Scaling Laws for Autoregressive Generative Modeling»

115 papers of our library cite it (of the 140,884 whose bibliographies we read) · 32 with a page here, the most cited first · ← the paper

1. On the Opportunities and Risks of Foundation ModelsRishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,044 citations
2. A Survey of Large Language ModelsWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,847 citations
3. Measuring Mathematical Problem Solving With the MATH DatasetDan Hendrycks, Collin Burns, Saurav Kadavath, et al.2021 · 2,318 citations
4. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsAarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.2022 · 1,695 citations
5. GPT-NeoX-20B: An Open-Source Autoregressive Language ModelSidney Black, Stella Biderman, Eric Hallahan, et al.2022 · 818 citations
6. Reproducible scaling laws for contrastive language-image learningMehdi Cherti, Romain Beaumont, Ross Wightman, et al.2022 · 750 citations
7. LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text PairsChristoph Schuhmann, Richard Vencu, Romain Beaumont, et al.2021 · 528 citations
8. Baichuan 2: Open Large-scale Language ModelsAiyuan Yang, Bin Xiao, Bingning Wang, et al.2023 · 512 citations
9. Yi: Open Foundation Models by 01.AIAlex Young, Bei Chen, Chao Li, et al.2024 · 402 citations
10. Are Emergent Abilities of Large Language Models a Mirage?Rylan Schaeffer, Brando Miranda, Sanmi Koyejo2023 · 323 citations
11. Faith and Fate: Limits of Transformers on CompositionalityNouha Dziri, Ximing Lu, Melanie Sclar, et al.2023 · 313 citations
12. Discovering Language Model Behaviors with Model-Written EvaluationsEthan Perez, Sam Ringer, Kamilė Lukošiūtė, et al.2022 · 305 citations
13. Scaling Laws for Reward Model OveroptimizationLeo Gao, John Schulman, Jacob Hilton2022 · 266 citations
14. Scaling Relationship on Learning Mathematical Reasoning with Large Language ModelsZheng Yuan, Hongyi Yuan, Chengpeng Li, et al.2023 · 252 citations
15. NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each BenchmarkOscar Sainz, Jon Campos, Iker García-Ferrero, et al.2023 · 245 citations
16. Beyond neural scaling laws: beating power law scaling via data pruningBen Sorscher, Robert Geirhos, Shashank Shekhar, et al.2022 · 220 citations
17. Search-o1: Agentic Search-Enhanced Large Reasoning ModelsXiaoxi Li, Guanting Dong, Jiajie Jin, et al.2025 · 205 citations
18. Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language ModelsKushal Tirumala, Aram H. Markosyan, Luke Zettlemoyer, et al.2022 · 183 citations
19. 8-bit Optimizers via Block-wise QuantizationTim Dettmers, Mike Lewis, Sam Shleifer, et al.2021 · 177 citations
20. Leveraging Large Language Models for Multiple Choice Question AnsweringJoshua Robinson, Christopher Michael Rytting, David Wingate2022 · 154 citations
21. The case for 4-bit precision: k-bit Inference Scaling LawsTim Dettmers, Luke Zettlemoyer2022 · 119 citations
22. Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language ModelsYangzhen Wu, Zhiqing Sun, Shanda Li, et al.2024 · 114 citations
23. Scaling Laws for TransferDanny Hernandez, Jared Kaplan, Tom Henighan, et al.2021 · 102 citations
24. SemDeDup: Data-efficient learning at web-scale through semantic deduplicationAmro Abbas, Kushal Tirumala, Dániel Simig, et al.2023 · 94 citations
25. Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?Yi Tay, Mostafa Dehghani, Samira Abnar, et al.2023 · 79 citations
26. Scaling Laws and Interpretability of Learning from Repeated DataDanny Hernandez, Tom Brown, Tom Conerly, et al.2022 · 62 citations
27. Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling LawsNikhil Sardana, Jacob Portes, Sasha Doubov, et al.2024 · 47 citations
28. Scaling Laws for Generative Mixed-Modal Language ModelsArmen Aghajanyan, Lili Yu, Alexis Conneau, et al.2023 · 39 citations
29. Observational Scaling Laws and the Predictability of Language Model PerformanceYangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto2024 · 28 citations
30. Distillation Scaling LawsDan Busbridge, Amitis Shidani, Floris Weers, et al.2025 · 23 citations
31. Resolving Discrepancies in Compute-Optimal Scaling of Language ModelsTomer Porian, Mitchell Wortsman, Jenia Jitsev, et al.2024 · 14 citations
32. Survey on Key Technologies for Large Language Model Pre-training Systems (大语言模型预训练系统关键技术综述)Yanjie Gao (高彦杰), Yueguo Chen (陈跃国)2025

83 more papers of our library cite it; they have no page here yet.

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/papers/henighan-2020-scaling-laws-autoregressive-generative-modeling/cited-by/