---
title: "Who cites Transcending Scaling Laws with 0.1% Extra Compute"
description: "35 papers of the Elamur Research library cite «Transcending Scaling Laws with 0.1% Extra Compute», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/tay-2022-transcending-scaling-laws-0-1/cited-by/"
---
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# Who cites «Transcending Scaling Laws with 0.1% Extra Compute»

35 papers of our library cite it (of the 141,840 whose bibliographies we read) · 11 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/tay-2022-transcending-scaling-laws-0-1/)

1. [**Scaling Instruction-Finetuned Language Models**Hyung Won Chung, Le Hou, Shayne Longpre, et al.*2022 · 3,339 citations*](https://md.research.elamur.ai/free/en/papers/chung-2022-scaling-instruction-finetuned-language-models/)
2. [**A Survey of Large Language Models**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,863 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/)
3. [**Emergent Abilities of Large Language Models**Jason Wei, Yi Tay, Rishi Bommasani, et al.*2022 · 2,229 citations*](https://md.research.elamur.ai/free/en/papers/wei-2022-emergent-abilities-large-language-models/)
4. [**A Comprehensive Overview of Large Language Models**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,286 citations*](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/)
5. [**Crosslingual Generalization through Multitask Finetuning**Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.*2022 · 695 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/)
6. [**The Flan Collection: Designing Data and Methods for Effective Instruction Tuning**Shayne Longpre, Le Hou, Tu Vu, et al.*2023 · 592 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-flan-collection-designing-data-methods/)
7. [**Galactica: A Large Language Model for Science**Ross Taylor, Marcin Kardas, Guillem Cucurull, et al.*2022 · 565 citations*](https://md.research.elamur.ai/free/en/papers/taylor-2022-galactica-large-language-model-science/)
8. [**The Falcon Series of Open Language Models**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 436 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/)
9. [**Challenges and Applications of Large Language Models**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
10. [**Pretraining Language Models with Human Preferences**Tomasz Korbak, Kejian Shi, Angelica Chen, et al.*2023 · 118 citations*](https://md.research.elamur.ai/free/en/papers/korbak-2023-pretraining-language-models-human-preferences/)
11. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/)

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

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