5 citations · 7 across the 9 of their papers we have counts for
6 papers · 1 filter
Thinking Outside the Bots: Human Ideas in AI's Semantic Blind Spots Are Not Inferior
Kibum Moon, Dan R. Johnson, Kostadin Kushlev +6
AI-generated outputs are frequently perceived as highly creative, but also tend to be more similar to each other (homogenized) than human ideas. Does the human heterogeneity that e…
AGC-Bench: Measuring Artificial General Creativity
Roger Beaty, Vijeta Deshpande, Clin K. Y. Lai +9
Creativity research has debated whether creativity is domain-specific (e.g., visual, writing, science), and if it is psychometrically separable from general intelligence. Both ques…
How LLMs See Creativity: Zero-Shot Scoring of Visual Creativity with Interpretable Reasoning
William Orwig, Roger E. Beaty
Evaluating the originality of visual images poses enduring challenges for creativity assessment. Automated scoring using AI models has proven effective in the verbal domain, yet ke…
Introducing multiplex semantic networks as multifaceted representations of creative associative knowledge across multilingual samples
Edith Haim, Kurt Haim, Roger E. Beaty +2
Creativity is a complex cognitive ability that relies on knowledge organisation and retrieval from semantic memory. Yet most research uses a single task to measure it, capturing on…
Playing with Words, Improving with Rewards: Training Language Models for Creative Association
Vijeta Deshpande, Namrata Shivagunde, Sherin Muckatira +5
Large Language Models (LLMs) are being applied to increasingly difficult problems and use cases. To navigate their vast solution spaces effectively, LLMs need to be creative. Yet t…
Large Language Models Align with the Human Brain during Creative Thinking
Mete Ismayilzada, Simone A. Luchini, Abdulkadir Gokce +5
Creative thinking is a fundamental aspect of human cognition, and divergent thinking-the capacity to generate novel and varied ideas-is widely regarded as its core generative engin…