How do people develop folk theories of generative AI text-to-image models?
This paper presents a qualitative study exploring how people develop folk theories to explain and understand generative AI text-to-image models.
How do people experience the images created by generative artificial intelligence?
This paper explores how people experience images created by generative AI, examining their perceptions, appraisals, and emotional responses to GenAI text-to-image models and their creations.
GENERAL: Generative, Explainable and Reasonable Artificial Learning
Introduction to the GENERAL workshop focusing on generative, explainable and reasonable artificial learning approaches.
Paint it, BLACK: A Novel Methodology for Prompting
This paper introduces BLACK, a novel methodology for prompting large language models and generative AI systems.
Stars, Stripes, and Silicon: Unravelling ChatGPT's All-American, Monochrome, Cis-Centric Bias
This paper investigates and reveals cultural, racial, and gender biases present in ChatGPT, examining its all-American, monochrome, and cis-centric tendencies.
How shall a machine call a thing?
This paper explores the concept of basicness in language through attention-based neural networks and human-in-the-loop methodology. Based on the Master’s thesis work.
NearMe: Dynamic Exploration of Geographical Areas
NearMe presents a novel approach to dynamic exploration of geographical areas, enabling users to interact with digital maps and discover nearby points of interest.