To address intricate real-world tasks, there has been a rising interest in tool utilization in
applications of large language models (LLMs). To develop LLM-based agents, it usually …

Large language models (LLMs) have been widely used as agents to complete different
tasks, such as personal assistance or event planning. While most work has focused on …

Evaluation of large language models (LLMs) has raised great concerns in the community
due to the issue of data contamination. Existing work designed evaluation protocols using …

A central aspect of machine learning research is experimentation, the process of designing
and running experiments, analyzing the results, and iterating towards some positive …

This study investigates the potential of Large Language Models (LLMs) to simulate human
group dynamics, particularly within politically charged contexts. We replicate the Wisdom of …

The current mainstream approach to train natural language systems is to expose them to
large amounts of text. This passive learning is problematic if we are interested in developing …

Recent advances in large language models (LLM) have enabled richer social simulations,
allowing for the study of various social phenomena. However, most recent work has used a …

The emergence of social norms has attracted much interest in a wide array of disciplines,
ranging from social science and cognitive science to artificial intelligence. In this paper, we …

Recent advancements in large language models (LLMs) have shown potential for human-
like agents. To help these agents adapt to new tasks without extensive human supervision …

We introduce Lumos, a novel framework for training language agents that employs a unified
data format and a modular architecture based on open-source large language models …