mlsanityData to 7 Oct 2026

The Design Space of Generative Models

arXiv 2304.10547 ↗First posted 15 Apr 2023cs.AI cs.HCcited by 9

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Abstract (arXiv)

Card et al.'s classic paper "The Design Space of Input Devices" established the value of design spaces as a tool for HCI analysis and invention. We posit that developing design spaces for emerging pre-trained, generative AI models is necessary for supporting their integration into human-centered systems and practices. We explore what it means to develop an AI model design space by proposing two design spaces relating to generative AI models: the first considers how HCI can impact generative models (i.e., interfaces for models) and the second considers how generative models can impact HCI (i.e., models as an HCI prototyping material).

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 10 of its 14 references that are in the map. First posted on arXiv 15 Apr 2023.

Builds on

10 of 14 references.

References · 10

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  3. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  4. 2021On the Opportunities and Risks of Foundation Modelscited by 3,961
  5. 2022LaMDA: Language Models for Dialog Applicationscited by 1,218
  6. 2022Social Simulacra: Creating Populated Prototypes for Social Computing Systemscited by 300
  7. 2021All That's 'Human' Is Not Gold: Evaluating Human Evaluation of Generated Textcited by 287
  8. 2021AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Promptscited by 265
  9. 2022LaMPost: Design and Evaluation of an AI-assisted Email Writing Prototype for Adults with Dyslexiacited by 27
  10. 2022Context-Aware Abbreviation Expansion Using Large Language Modelscited by 5

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Cited by year

Citing papers per year: 2023: 2; 2024: 6; 2025: 1.

9 papers.