---
title: "Who cites Edward Hughes — 62 papers of our library"
description: "62 papers of the Elamur Research library cite the works of Edward Hughes, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/edward-hughes/cited-by/"
---
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# Who cites Edward Hughes

62 citations of their works from 62 papers of our library (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · [← Edward Hughes](https://md.research.elamur.ai/free/en/authors/edward-hughes/)

1. [**Training language models to follow instructions with human feedback arXiv:2203.02155**Long Ouyang, Jeff Wu, Xu Jiang, et al.*2022 · 10,224 citations*](https://md.research.elamur.ai/free/en/papers/ouyang-2022-training-language-models-follow-instructions/)
2. [**On the Opportunities and Risks of Foundation Models arXiv:2108.07258**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,160 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/)
3. **[A Survey of Reinforcement Learning Informed by Natural Language](https://md.research.elamur.ai/free/en/papers/luketina-2019-survey-reinforcement-learning-informed-natural/) [International Joint Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/international-joint-conference-on-artificial-intelligence/)**Jelena Luketina, Nantas Nardelli, Gregory Farquhar, et al.*2019 · 231 citations*
4. [**Scalable agent alignment via reward modeling: a research direction arXiv:1811.07871**Jan Leike, David Krueger, Tom Everitt, et al.*2018 · 227 citations*](https://md.research.elamur.ai/free/en/papers/leike-2018-scalable-agent-alignment-reward-modeling/)
5. [**RRHF: Rank Responses to Align Language Models with Human Feedback without tears arXiv:2304.05302**Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.*2023 · 201 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-rrhf-rank-responses-align-language/)
6. [**BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions arXiv:2406.15877**Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.*2024 · 176 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2024-bigcodebench-benchmarking-code-generation-diverse/)
7. [**BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning arXiv:1810.08272**Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou, et al.*2018 · 123 citations*](https://md.research.elamur.ai/free/en/papers/chevalier-boisvert-2018-babyai-platform-study-sample-efficiency/)
8. [**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/)
9. **[Absolute Zero: Reinforced Self-play Reasoning with Zero Data](https://md.research.elamur.ai/free/en/papers/zhao-2025-absolute-zero-reinforced-self-play/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Andrew Zhao, Yiran Wu, Yang Yue, et al.*2025 · 57 citations*
10. [**Darwin Godel Machine: Open-Ended Evolution of Self-Improving Agents arXiv:2505.22954**Jenny Zhang, Shengran Hu, Cong Lu, et al.*2025 · 47 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-darwin-godel-machine-open/)
11. [**CLIN: A Continually Learning Language Agent for Rapid Task Adaptation and Generalization arXiv:2310.10134**Bodhisattwa Prasad Majumder, Bhavana Dalvi Mishra, Peter Jansen, et al.*2023 · 34 citations*](https://md.research.elamur.ai/free/en/papers/majumder-2023-clin-continually-learning-language-agent/)
12. [**Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models arXiv:2412.02980**Alex Havrilla, Andrew Dai, Laura O'Mahony, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-surveying-effects-quality-diversity-complexity/)
13. [**OMNI-EPIC: Open-endedness via Models of human Notions of Interestingness with Environments Programmed in Code arXiv:2405.15568**Maxence Faldor, Jenny Zhang, Antoine Cully, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/faldor-2024-omni-epic-open-endedness-models/)
14. [**Augmenting Autotelic Agents with Large Language Models arXiv:2305.12487**Cedric Colas, Laetitia Teodorescu, Pierre-Yves Oudeyer, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/colas-2023-augmenting-autotelic-agents-large-language/)
15. [**Distilling Internet-Scale Vision-Language Models into Embodied Agents arXiv:2301.12507**Theodore Sumers, Kenneth Marino, Arun Ahuja, et al.*2023 · 9 citations*](https://md.research.elamur.ai/free/en/papers/sumers-2023-distilling-internet-scale-vision-language/)
16. **[CreativeBench: Benchmarking and Enhancing Machine Creativity via Self-Evolving Challenges](https://md.research.elamur.ai/free/en/papers/wang-2026-creativebench-benchmarking-enhancing-machine-creativity/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zihan Wang, Lam Nguyen, Zhengyang Zhao, et al.*2026 · 6 citations*
17. [**Training AI Scientists to Replicate Research arXiv:2608.13331**Damon Falck, Samer Sabri, Anja Surina, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/falck-2026-training-ai-scientists-replicate/)
18. **[On Safety Risks in Experience-Driven Self-Evolving Agents](https://md.research.elamur.ai/free/en/papers/zhao-2026-safety-risks-experience-driven-self/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weixiang Zhao, Yichen Zhang, Yingshuo Wang, et al.*2026 · 1 citation*

44 more citing papers of our library have no page here yet.

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