About the Journal

The Journal of Generative Intelligence (JGI) is a peer-reviewed, open-access journal on generative artificial intelligence. It covers the models themselves, including GANs, variational autoencoders, diffusion models and large language models, along with the methods used to train, evaluate and control them and the applications they are changing.

We want papers that teach the field something it did not know: a clearer account of why a model behaves as it does, an honest evaluation on a hard task, or a careful application in language, vision, science or the creative arts. Work on the safe and responsible use of generative systems is a core part of the journal, not an afterthought.

Aim & Scope

  • Generative models: GANs, VAEs, diffusion and flow-based models
  • Large language models, text generation and dialogue systems
  • Image, video and audio synthesis
  • Multimodal generation and cross-modal translation
  • Evaluation, benchmarking and robustness of generative systems
  • Synthetic data and data augmentation
  • Generative AI in the creative arts, design and media
  • Safety, alignment and responsible deployment of generative AI

Journal Information

  • Title: Journal of Generative Intelligence (JGI)
  • Editor-in-Chief: Dr. Sergey Garchenko
  • e-ISSN: 3117-6429  |  p-ISSN: 3117-6437
  • Publisher: GalaxiaUniverse, Taurusavenue 105, 2122 LS Hoofddorp, Netherlands
  • First published: 2024
  • Frequency: Quarterly
  • Country: Netherlands
  • Peer review: Double-blind, by at least two independent reviewers
  • Licence: CC BY 4.0; authors keep their copyright
  • Article Processing Charges: see APC rates and waivers
  • Indexing: Google Scholar
  • Language: English
  • Contact: galaxiauniverse1986@gmail.com