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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Generative Adversarial Network Rooms in Generative Graph Grammar Dungeons for The Legend of Zelda
Jake Gutierrez, Jacob Schrum
2022 IEEE Congress on Evolutionary Computation (CEC) (2020), pp. 1-8
Open Access | Times Cited: 33

Showing 1-25 of 33 citing articles:

Procedural game level generation with GANs: potential, weaknesses, and unresolved challenges in the literature
Daniele Fernandes E. Silva, Rafael Torchelsen, Marílton Sanchotene de Aguiar
Multimedia Tools and Applications (2025)
Closed Access | Times Cited: 1
Generative Adversarial Networks–Enabled Human–Artificial Intelligence Collaborative Applications for Creative and Design Industries: A Systematic Review of Current Approaches and Trends
Rowan T. Hughes, Liming Zhu, Tomasz Bednarz
Frontiers in Artificial Intelligence (2021) Vol. 4
Open Access | Times Cited: 79
Integrating AIGC with design: dependence, application, and evolution - a systematic literature review
Jianfeng Wu, Yuting Cai, Tingyu Sun, et al.
Journal of Engineering Design (2024), pp. 1-39
Closed Access | Times Cited: 6
Sequential Segment-based Level Generation and Blending using Variational Autoencoders
Anurag Sarkar, Seth Cooper
(2020)
Open Access | Times Cited: 29
Procedural Dungeon Generation: A Survey
Breno M. F. Viana, Selan Rodrigues dos Santos
Journal on Interactive Systems (2021) Vol. 12, Iss. 1, pp. 83-101
Open Access | Times Cited: 21
Deep learning for procedural content generation
Jialin Liu, Sam Snodgrass, Ahmed Khalifa, et al.
Neural Computing and Applications (2020) Vol. 33, Iss. 1, pp. 19-37
Open Access | Times Cited: 21
Towards Game Design via Creative Machine Learning (GDCML)
Anurag Sarkar, Seth Cooper
2021 IEEE Conference on Games (CoG) (2020), pp. 744-751
Open Access | Times Cited: 20
World-GAN: a Generative Model for Minecraft Worlds
Maren Awiszus, Frederik Schubert, Bodo Rosenhahn
2021 IEEE Conference on Games (CoG) (2021), pp. 1-8
Open Access | Times Cited: 17
Capturing Local and Global Patterns in Procedural Content Generation via Machine Learning
Vanessa Volz, Niels Justesen, Sam Snodgrass, et al.
2021 IEEE Conference on Games (CoG) (2020), pp. 399-406
Open Access | Times Cited: 15
Dungeon and Platformer Level Blending and Generation using Conditional VAEs
Anurag Sarkar, Seth Cooper
2021 IEEE Conference on Games (CoG) (2021), pp. 1-8
Open Access | Times Cited: 12
Social Paradigm Shift Promoted by Generative Models: A Study on the Trend from Result-Oriented to Process-Oriented Paradigm
Bin Zhou
(2024)
Open Access | Times Cited: 1
Dungeon level generation using generative adversarial network: an experimental study for top-down view games
Daniele Fernandes e Silva, Rafael Torchelsen, Marílton Sanchotene de Aguiar
(2023), pp. 95-106
Open Access | Times Cited: 3
A Novel CNet-assisted Evolutionary Level Repairer and Its Applications to Super Mario Bros
Tianye Shu, Ziqi Wang, Jialin Liu, et al.
2022 IEEE Congress on Evolutionary Computation (CEC) (2020), pp. 1-10
Open Access | Times Cited: 7
Hybrid Encoding for Generating Large Scale Game Level Patterns With Local Variations
Jacob Schrum, Benjamin Capps, Kirby Steckel, et al.
IEEE Transactions on Games (2022) Vol. 15, Iss. 1, pp. 46-55
Open Access | Times Cited: 4
Wor(l)d-GAN: Toward Natural-Language-Based PCG in Minecraft
Maren Awiszus, Frederik Schubert, Bodo Rosenhahn
IEEE Transactions on Games (2022) Vol. 15, Iss. 2, pp. 182-192
Closed Access | Times Cited: 3
Player-Oriented Procedural Generation: Producing Desired Game Content by Natural Language
Binlin Feng, MingYang Su, Keyi Zeng, et al.
Lecture notes in computer science (2024), pp. 260-274
Closed Access
G-PCGRL: Procedural Graph Data Generation via Reinforcement Learning
Florian Rupp, Kai Eckert
2021 IEEE Conference on Games (CoG) (2024), pp. 1-8
Closed Access
Creating a Newer and Improved Procedural Content Generation (PCG) Algorithm with Minimal Human Intervention for Computer Gaming Development
Lazaros Lazaridis, George F. Fragulis
Computers (2024) Vol. 13, Iss. 11, pp. 304-304
Open Access
An analysis of DOOM level generation using Generative Adversarial Networks
Edoardo Giacomello, Pier Luca Lanzi, Daniele Loiacono
Entertainment Computing (2023) Vol. 46, pp. 100549-100549
Open Access | Times Cited: 1
Procedural generation of virtual pavilions via a deep convolutional generative adversarial network
Ziwei Chen, Desheng Lyu
Computer Animation and Virtual Worlds (2022) Vol. 33, Iss. 3-4
Closed Access | Times Cited: 2
Toward Co-creative Dungeon Generation via Transfer Learning
Zisen Zhou, Matthew Guzdial
(2021), pp. 1-9
Open Access | Times Cited: 2
Adaptação do processo ENgAGED para o desenvolvimento de conteúdos curriculares em uma plataforma de jogos baseada em Gramática de Grafos
Júlia Veiga da Silva, Braz Araujo da Silva, Luciana Foss, et al.
Anais do XXXII Simpósio Brasileiro de Informática na Educação (SBIE 2021) (2021), pp. 316-327
Open Access | Times Cited: 2
Using Multiple Generative Adversarial Networks to Build Better-Connected Levels for Mega Man
Benjamin Capps, Jacob Schrum
arXiv (Cornell University) (2021)
Closed Access | Times Cited: 2
Auto Generating Maps in a 2D Environment
Lazaros Lazaridis, Konstantinos-Filippos Kollias, George S. Maraslidis, et al.
Lecture notes in computer science (2022), pp. 40-50
Closed Access | Times Cited: 1
Orchestrating and Adapting of Dungeon Levels, Locked-door Missions, and Enemies
Breno Mauricio de Freitas Viana
(2022)
Open Access | Times Cited: 1
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