no code implementations • 2 Jan 2018 • Pegah Karimi, Nicholas Davis, Kazjon Grace, Mary Lou Maher
We present a system for identifying conceptual shifts between visual categories, which will form the basis for a co-creative drawing system to help users draw more creative sketches.
no code implementations • 25 Jul 2018 • Pegah Karimi, Kazjon Grace, Mary Lou Maher, Nicholas Davis
This paper provides a framework for evaluating creativity in co-creative systems: those that involve computer programs collaborating with human users on creative tasks.
no code implementations • 24 Jun 2019 • Pegah Karimi, Mary Lou Maher, Nicholas Davis, Kazjon Grace
This paper presents a computational model for conceptual shifts, based on a novelty metric applied to a vector representation generated through deep learning.
no code implementations • 15 Apr 2022 • Jeba Rezwana, Mary Lou Maher
There is relatively little research about interaction design in the co-creativity field, which is reflected in a lack of focus on interaction design in many existing co-creative systems.
no code implementations • 15 Apr 2022 • Jeba Rezwana, Mary Lou Maher
Human-AI co-creativity involves humans and AI collaborating on a shared creative product as partners.
no code implementations • 27 Apr 2022 • Jeba Rezwana, Mary Lou Maher
Typically, the AI in co-creative systems cannot communicate back to humans, limiting their potential to be perceived as partners rather than just a tool.
no code implementations • 29 Dec 2023 • Dhruv Dhamani, Mary Lou Maher
The paper discusses the implications of this lens, for the cross-pollination of research between LLM prompting and LLM-based multi-agent systems; and also, for the generation of synthetic training data based on existing prompting techniques in research.
no code implementations • 29 Feb 2024 • Sri Yash Tadimalla, Mary Lou Maher
In this context, This paper examines the intersection of AI and identity as a pathway to understand biases, inequalities, and ethical considerations in AI development and deployment.
