Computer SciencePLOS ONE
Evaluating the capacity of large language models to interpret emotions in images
H. Alrasheed, A. Alghihab, et al.
Discover how GPT-4 can streamline emotional stimulus selection by rating visual images on valence and arousal, closely approximating human judgments under zero-shot conditions while noting challenges with subtler cues. This research was conducted by Hend Alrasheed, Adwa Alghihab, Alex Pentland, and Sharifa Alghowinem.
Related Publications
Explore these studies to deepen your understanding
Adjacent work that informs or extends this paper's methodology and findings.
Psychology
Understanding the Role of Large Language Models in Personalizing and Scaffolding Strategies to Combat Academic Procrastination
A. Bhattacharjee, Y. Zeng, et al.
Psychology
Understanding the Role of Large Language Models in Personalizing and Scaffolding Strategies to Combat Academic Procrastination
A. Bhattacharjee, Y. Zeng, et al.
Interdisciplinary Studies
Analyzing Memory Effects in Large Language Models through the Lens of Cognitive Psychology
Z. Cao, L. Schooler, et al.
Computer Science
Sentiment Analysis in the Era of Large Language Models: A Reality Check
W. Zhang, Y. Deng, et al.
