---
title: "Who cites Deep Reinforcement Learning at — 49 citing papers"
description: "49 papers of the Elamur Research library cite «Deep Reinforcement Learning at the Edge of the Statistical Precipice», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/agarwal-2021-deep-reinforcement-learning-edge-statistical/cited-by/"
---
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# Who cites «Deep Reinforcement Learning at the Edge of the Statistical Precipice»

49 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · [← back to «Deep Reinforcement Learning at the Edge of the Statistical Precipice»](https://md.research.elamur.ai/free/en/papers/agarwal-2021-deep-reinforcement-learning-edge-statistical/)

1. [**Large Language Models Are Human-Level Prompt Engineers arXiv:2211.01910**Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, et al.*2022 · 701 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2022-large-language-models-human-level/)
2. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
3. **[Quark: Controllable Text Generation with Reinforced Unlearning](https://md.research.elamur.ai/free/en/papers/lu-2022-quark-controllable-text-generation-reinforced/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ximing Lu, Sean Welleck, Jack Hessel, et al.*2022 · 170 citations*
4. **[Efficient Methods for Natural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/treviso-2023-efficient-methods-natural-language-processing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Marcos Treviso, Ji-Ung Lee, Tianchu Ji, et al.*2023 · 145 citations*
5. [**Eureka: Human-Level Reward Design via Coding Large Language Models arXiv:2310.12931**Yecheng Jason Ma, William Liang, Guanzhi Wang, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-eureka-human-level-reward-design/)
6. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/agarwal-2021-deep-reinforcement-learning-edge-statistical/) — Deep Reinforcement Learning at the Edge of the Statistical Precipice