mlsanityData to 14 Oct 2026

Creativity in AI: Progresses and Challenges

arXiv 2410.17218 ↗First posted 22 Oct 2024cs.AI cs.CLcited by 7

Not on the map. Why?

Abstract (arXiv)

Creativity is the ability to produce novel, useful, and surprising ideas, and has been widely studied as a crucial aspect of human cognition. Machine creativity on the other hand has been a long-standing challenge. With the rise of advanced generative AI, there has been renewed interest and debate regarding AI's creative capabilities. Therefore, it is imperative to revisit the state of creativity in AI and identify key progresses and remaining challenges. In this work, we survey leading works studying the creative capabilities of AI systems, focusing on creative problem-solving, linguistic, artistic, and scientific creativity. Our review suggests that while the latest AI models are largely capable of producing linguistically and artistically creative outputs such as poems, images, and musical pieces, they struggle with tasks that require creative problem-solving, abstract thinking and compositionality and their generations suffer from a lack of diversity, originality, long-range incoherence and hallucinations. We also discuss key questions concerning copyright and authorship issues with generative models. Furthermore, we highlight the need for a comprehensive evaluation of creativity that is process-driven and considers several dimensions of creativity. Finally, we propose future research directions to improve the creativity of AI outputs, drawing inspiration from cognitive science and psychology.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 218 of its 474 references that are in the map. First posted on arXiv 22 Oct 2024.

Builds on

218 of 474 references.

References · 218

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  5. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  6. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
  7. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
  8. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 6,013
  9. 2022Generative Adversarial Networkscited by 5,627
  10. 2021Zero-Shot Text-to-Image Generationcited by 4,288
  11. 2022Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackcited by 3,720
  12. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,614
38 more
  1. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,588
  2. 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,474
  3. 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,300
  4. 2019The Curious Case of Neural Text Degenerationcited by 2,916
  5. 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,694
  6. 2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,611
  7. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,592
  8. 2020Extracting Training Data from Large Language Modelscited by 2,189
  9. 2014Conditional Generative Adversarial Netscited by 2,162
  10. 2015Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networkscited by 2,054
  11. 2016Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Networkcited by 1,908
  12. 2022Imagen Video: High Definition Video Generation with Diffusion Modelscited by 1,778
  13. 2022Make-A-Video: Text-to-Video Generation without Text-Video Datacited by 1,742
  14. 2021ViViT: A Video Vision Transformercited by 1,620
  15. 2016Context Encoders: Feature Learning by Inpaintingcited by 1,428
  16. 2018Hierarchical Neural Story Generationcited by 1,193
  17. 2016Colorful Image Colorizationcited by 1,114
  18. 2024The AI Scientist: Towards Fully Automated Open-Ended Scientific Discoverycited by 1,071
  19. 2021StyleCLIP: Text-Driven Manipulation of StyleGAN Imagerycited by 991
  20. 2018The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networkscited by 864
  21. 2016Conditional Image Generation with PixelCNN Decoderscited by 862
  22. 2016Pixel Recurrent Neural Networkscited by 816
  23. 2019Plug and Play Language Models: A Simple Approach to Controlled Text Generationcited by 799
  24. 2018Multimodal Unsupervised Image-to-Image Translationcited by 795
  25. 2016Generative Adversarial Text to Image Synthesiscited by 735
  26. 2020Encoding in Style: a StyleGAN Encoder for Image-to-Image Translationcited by 727
  27. 2019Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?cited by 675
  28. 2021VideoGPT: Video Generation using VQ-VAE and Transformerscited by 658
  29. 2022Contrastive Decoding: Open-ended Text Generation as Optimizationcited by 609
  30. 2020Jukebox: A Generative Model for Musiccited by 542
  31. 2022Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionalitycited by 529
  32. 2017MoCoGAN: Decomposing Motion and Content for Video Generationcited by 524
  33. 2023Faith and Fate: Limits of Transformers on Compositionalitycited by 503
  34. 2023VideoPoet: A Large Language Model for Zero-Shot Video Generationcited by 492
  35. 2022Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priorscited by 487
  36. 2015A Neural Algorithm of Artistic Stylecited by 483
  37. 2023MusicLM: Generating Music From Textcited by 448
  38. 2022Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Modelscited by 424

50 most cited of 218 All 218 (JSON)

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 5.

7 papers.

  1. 2025Societal Impacts Research Requires Benchmarks for Creative Composition Taskscited by 3
  2. 2026The Homogenization Problem in LLMs: Towards Meaningful Diversity in AI Safetycited by 2
  3. 2026The Art That Poses Back: Assessing AI Pastiches after Contemporary Artworkscited by 1
  4. 2025AssoCiAm: A Benchmark for Evaluating Association Thinking while Circumventing Ambiguitycited by 0
  5. 2026CresOWLve: Benchmarking Creative Problem-Solving Over Real-World Knowledgecited by 0
  6. 2026Large Language Models Align with the Human Brain during Creative Thinkingcited by 0
  7. 2026IDEAFix: Evaluation Framework for Creative Defixation Prompting in LLMscited by 0