Luminate: Structured Generation and Exploration of Design Space with Large Language Models for Human-AI Co-Creation
University of California San Diego · University of Notre Dame
Abstract
Thanks to their generative capabilities, large language models (LLMs) have become an invaluable tool for creative processes. These models have the capacity to produce hundreds and thousands of visual and textual outputs, offering abundant inspiration for creative endeavors. But are we harnessing their full potential? We argue that current interaction paradigms fall short, guiding users towards rapid convergence on a limited set of ideas, rather than empowering them to explore the vast latent design space in generative models. To address this limitation, we propose a framework that facilitates the structured generation of design space in which users can seamlessly explore, evaluate, and synthesize a multitude…
Citation impact
- FWCI
- 34.44
- Percentile
- 100%
- References
- 60
Authors
5Topics & keywords
- Generative grammar
- Computer science
- Set (abstract data type)
- Space (punctuation)
- Multitude
- Human–computer interaction
- Data science
- Artificial intelligence
- Quality Education