3 papers
cs.CL2026
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…
cs.CL2026
Evaluating Text Creativity across Diverse Domains: A Dataset and Large Language Model Evaluator
Qian Cao, Xiting Wang, Yuzhuo Yuan +3
Creativity evaluation remains a challenging frontier for large language models (LLMs). Current evaluations heavily rely on inefficient and costly human judgments, hindering progres…
cs.AI2024
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…