51 citations · 122 across the 19 of their papers we have counts for
6 papers · 1 filter
Be.FM: Open Foundation Models for Human Behavior
Yutong Xie, Zhuoheng Li, Xiyuan Wang +10
Despite their success in numerous fields, the potential of foundation models for modeling and understanding human behavior remains largely unexplored. We introduce Be.FM, one of th…
Using Large Language Models to Categorize Strategic Situations and Decipher Motivations Behind Human Behaviors
Yutong Xie, Qiaozhu Mei, Walter Yuan +1
By varying prompts to a large language model, we can elicit the full range of human behaviors in a variety of different scenarios in classic economic games. By analyzing which prom…
How Different AI Chatbots Behave? Benchmarking Large Language Models in Behavioral Economics Games
Yutong Xie, Yiyao Liu, Zhuang Ma +5
The deployment of large language models (LLMs) in diverse applications requires a thorough understanding of their decision-making strategies and behavioral patterns. As a supplemen…
MapExplorer: New Content Generation from Low-Dimensional Visualizations
Xingjian Zhang, Ziyang Xiong, Shixuan Liu +6
Low-dimensional visualizations, or "projection maps," are widely used in scientific and creative domains to interpret large-scale and complex datasets. These visualizations not onl…
Bridging AI and Science: Implications from a Large-Scale Literature Analysis of AI4Science
Yutong Xie, Yijun Pan, Hua Xu +1
Artificial Intelligence has proven to be a transformative tool for advancing scientific research across a wide range of disciplines. However, a significant gap still exists between…
A Turing Test: Are AI Chatbots Behaviorally Similar to Humans?
Qiaozhu Mei, Yutong Xie, Walter Yuan +1
We administer a Turing Test to AI Chatbots. We examine how Chatbots behave in a suite of classic behavioral games that are designed to elicit characteristics such as trust, fairnes…