22 citations · 48 across the 9 of their papers we have counts for
9 papers
Position: We Need Large Language Models Optimized For Our Well-Being
Ashton Anderson, Harsh Kumar, Louis Tay +1
Large language models are useful because we taught them to give us what we want. This works when success can be judged immediately, but people increasingly bring these systems thei…
Diagnosing and Repairing Persona Collapse in LLM Advice
Harsh Kumar, Karina Vold, Louis Tay +1
A good advisor comforts someone in crisis, challenges someone in denial, and gives practical guidance on a logistical question. We ask whether large language models (LLMs) vary the…
Understanding Critical Thinking in Generative Artificial Intelligence Use: Development, Validation, and Correlates of the Critical Thinking in AI Use Scale
Gabriel R. Lau, Wei Yan Low, Louis Tay +3
Generative AI tools are increasingly embedded in everyday work and learning, yet their fluency, opacity, and propensity to hallucinate mean that users must critically evaluate AI o…
When AI Gives Advice: Evaluating AI and Human Responses to Online Advice-Seeking for Well-Being
Harsh Kumar, Jasmine Chahal, Yinuo Zhao +4
Seeking advice is a core human behavior that the internet has reinvented twice: first through forums and Q&A communities that crowdsource public guidance, and now through large lan…
Robust Bias Detection in MLMs and its Application to Human Trait Ratings
Ingroj Shrestha, Louis Tay, Padmini Srinivasan
There has been significant prior work using templates to study bias against demographic attributes in MLMs. However, these have limitations: they overlook random variability of tem…
Language-based Valence and Arousal Expressions between the United States and China: a Cross-Cultural Examination
Young-Min Cho, Dandan Pang, Stuti Thapa +4
While affective expressions on social media have been extensively studied, most research has focused on the Western context. This paper explores cultural differences in affective e…
Integrating Psychometrics and Computing Perspectives on Bias and Fairness in Affective Computing: A Case Study of Automated Video Interviews
Brandon M Booth, Louis Hickman, Shree Krishna Subburaj +3
We provide a psychometric-grounded exposition of bias and fairness as applied to a typical machine learning pipeline for affective computing. We expand on an interpersonal communic…
Studying Politeness across Cultures Using English Twitter and Mandarin Weibo
Mingyang Li, Louis Hickman, Louis Tay +2
Modeling politeness across cultures helps to improve intercultural communication by uncovering what is considered appropriate and polite. We study the linguistic features associate…
Studying Cultural Differences in Emoji Usage across the East and the West
Sharath Chandra Guntuku, Mingyang Li, Louis Tay +1
Global acceptance of Emojis suggests a cross-cultural, normative use of Emojis. Meanwhile, nuances in Emoji use across cultures may also exist due to linguistic differences in expr…