12 citations · 20 across the 7 of their papers we have counts for
8 papers
Rationality Check! Benchmarking the Rationality of Large Language Models
Zhilun Zhou, Jing Yi Wang, Nicholas Sukiennik +4
Large language models (LLMs), a recent advance in deep learning and machine intelligence, have manifested astonishing capacities, now considered among the most promising for artifi…
Debiasing International Attitudes: LLM Agents for Simulating US-China Perception Changes
Nicholas Sukiennik, Yichuan Xu, Yuqing Kan +4
Large Language Models (LLMs) offer transformative opportunities to address the longstanding challenge of modeling opinion evolution in computational social science. This study inve…
AI Agent Behavioral Science
Lin Chen, Yunke Zhang, Jie Feng +13
Recent advances in large language models (LLMs) have enabled the development of AI agents that exhibit increasingly human-like behaviors, including planning, adaptation, and social…
An Evaluation of Cultural Value Alignment in LLM
Nicholas Sukiennik, Chen Gao, Fengli Xu +1
LLMs as intelligent agents are being increasingly applied in scenarios where human interactions are involved, leading to a critical concern about whether LLMs are faithful to the v…
Simulating Filter Bubble on Short-video Recommender System with Large Language Model Agents
Nicholas Sukiennik, Haoyu Wang, Zailin Zeng +2
An increasing reliance on recommender systems has led to concerns about the creation of filter bubbles on social media, especially on short video platforms like TikTok. However, th…
A Survey on Human-Centric LLMs
Jing Yi Wang, Nicholas Sukiennik, Tong Li +6
The rapid evolution of large language models (LLMs) and their capacity to simulate human cognition and behavior has given rise to LLM-based frameworks and tools that are evaluated…
Understanding World or Predicting Future? A Comprehensive Survey of World Models
Jingtao Ding, Yunke Zhang, Yu Shang +12
The concept of world models has garnered significant attention due to advancements in multimodal large language models such as GPT-4 and video generation models such as Sora, which…
Uncovering the Deep Filter Bubble: Narrow Exposure in Short-Video Recommendation
Nicholas Sukiennik, Chen Gao, Nian Li
Filter bubbles have been studied extensively within the context of online content platforms due to their potential to cause undesirable outcomes such as user dissatisfaction or pol…