---
title: "Who cites RL²: Fast Reinforcement Learning — 67 citing papers"
description: "67 papers of the Elamur Research library cite «RL²: Fast Reinforcement Learning via Slow Reinforcement Learning», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/duan-2016-rl-2-fast-reinforcement-learning/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/duan-2016-rl-2-fast-reinforcement-learning/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [RL²: Fast Reinforcement Learning via Slow…](https://md.research.elamur.ai/free/en/papers/duan-2016-rl-2-fast-reinforcement-learning/) / cited by

# Who cites «RL²: Fast Reinforcement Learning via Slow Reinforcement Learning»

67 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 «RL²: Fast Reinforcement Learning via Slow Reinforcement Learning»](https://md.research.elamur.ai/free/en/papers/duan-2016-rl-2-fast-reinforcement-learning/)

1. [**Language Models are Few-Shot Learners arXiv:2005.14165**Tom B. Brown, Benjamin Mann, Nick Ryder, et al.*2020 · 14,178 citations*](https://md.research.elamur.ai/free/en/papers/brown-2020-language-models-few-shot-learners/)
2. **[Learning Transferable Architectures for Scalable Image Recognition](https://md.research.elamur.ai/free/en/papers/zoph-2017-learning-transferable-architectures-scalable-image/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Barret Zoph, Vijay Vasudevan, Jonathon Shlens, et al.*2017 · 6,583 citations*
3. [**Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks arXiv:1703.03400**Chelsea Finn, Pieter Abbeel, Sergey Levine*2017 · 6,549 citations*](https://md.research.elamur.ai/free/en/papers/finn-2017-model-agnostic-meta-learning-fast/)
4. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,272 citations*
5. [**A Review of Large Language Models and Autonomous Agents in Chemistry arXiv:2407.01603**Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White*2024 · 288 citations*](https://md.research.elamur.ai/free/en/papers/ramos-2024-review-large-language-models-autonomous/)
6. [**Kevin: Multi-Turn RL for Generating CUDA Kernels arXiv 2025**Carlo Baronio, Pietro Marsella, Ben Pan, et al.*2025 · 69 citations*](https://md.research.elamur.ai/free/en/papers/baronio-2025-kevin-multi-turn-rl-generating/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/duan-2016-rl-2-fast-reinforcement-learning/) — RL²: Fast Reinforcement Learning via Slow Reinforcement Learning
