133 citations · 414 across the 25 of their papers we have counts for
6 papers · 1 filter
Seeing Like an AI: How LLMs Apply (and Misapply) Wikipedia Neutrality Norms
Joshua Ashkinaze, Ruijia Guan, Laura Kurek +3
Large language models (LLMs) are trained on broad corpora and then used in communities with specialized norms. Is providing LLMs with community rules enough for models to follow th…
Exploring Bridges Between Algorithmic and AI-generated Art
Jiaqi Wu, Eytan Adar
In this paper, we bridge algorithmic and AI art by adding functionality to the creative coding environment. We create two systems that demonstrate how AI features can enhance algor…
One vs. Many: Comprehending Accurate Information from Multiple Erroneous and Inconsistent AI Generations
Yoonjoo Lee, Kihoon Son, Tae Soo Kim +4
As Large Language Models (LLMs) are nondeterministic, the same input can generate different outputs, some of which may be incorrect or hallucinated. If run again, the LLM may corre…
Feminist Interaction Techniques: Deterring Non-Consensual Screenshots with Interaction Techniques
Li Qiwei, Francesca Lameiro, Shefali Patel +4
Non-consensual Intimate Media (NCIM) refers to the distribution of sexual or intimate content without consent. NCIM is common and causes significant emotional, financial, and reput…
Imagine a dragon made of seaweed: How images enhance learning in Wikipedia
Anita Silva, Maria Tracy, Katharina Reinecke +2
Though images are ubiquitous across Wikipedia, it is not obvious that the image choices optimally support learning. When well selected, images can enhance learning by dual coding,…
Authors' Values and Attitudes Towards AI-bridged Scalable Personalization of Creative Language Arts
Taewook Kim, Hyomin Han, Eytan Adar +2
Generative AI has the potential to create a new form of interactive media: AI-bridged creative language arts (CLA), which bridge the author and audience by personalizing the author…