8 citations · 9 across the 4 of their papers we have counts for
5 papers
Multi-agent AI systems outperform human teams in creativity
Tiancheng Hu, Yixuan Jiang, Haotian Li +5
Although artificial intelligence (AI) now matches or exceeds human performance across numerous cognitive tasks, creativity remains a highly contested frontier. As AI systems based…
Augmenting Rating-Scale Measures with Text-Derived Items Using the Information-Determined Scoring (IDS) Framework
Joe Watson, Ivan O'Connor, Chia-Wen Chen +3
Psychological assessments commonly rely on rating-scale items, which require respondents to condense complex experiences into predefined categories. Although rich, unstructured tex…
General Scales Unlock AI Evaluation with Explanatory and Predictive Power
Lexin Zhou, Lorenzo Pacchiardi, Fernando Martínez-Plumed +23
Ensuring safe and effective use of AI requires understanding and anticipating its performance on novel tasks, from advanced scientific challenges to transformed workplace activitie…
Large Language Models show both individual and collective creativity comparable to humans
Luning Sun, Yuzhuo Yuan, Yuan Yao +6
Artificial intelligence has, so far, largely automated routine tasks, but what does it mean for the future of work if Large Language Models (LLMs) show creativity comparable to hum…
Evaluating General-Purpose AI with Psychometrics
Xiting Wang, Liming Jiang, Jose Hernandez-Orallo +4
Comprehensive and accurate evaluation of general-purpose AI systems such as large language models allows for effective mitigation of their risks and deepened understanding of their…