3 citations · 6 across the 4 of their papers we have counts for
6 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…
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…