Large Language Models (LLMs) have achieved remarkable success across a wide array of
tasks. Due to the impressive planning and reasoning abilities of LLMs, they have been used …

Agents built with large language models (LLMs) have recently achieved great
advancements. However, most of the efforts focus on single-agent or cooperative settings …

Offline-to-online reinforcement learning (RL) is a training paradigm that combines pre-
training on a pre-collected dataset with fine-tuning in an online environment. However, the …

The swift evolution of Large-scale Models (LMs), either language-focused or multi-modal,
has garnered extensive attention in both academy and industry. But despite the surge in …

This paper aims to investigate the open research problem of uncovering the social
behaviors of LLM-based agents. To achieve this goal, we adopt Avalon, a representative …

Large Language Model (LLM) agents have been increasingly adopted as simulation tools to
model humans in applications such as social science. However, one fundamental question …

Inspired by the rapid development of Large Language Models (LLMs), LLM agents have
evolved to perform complex tasks. LLM agents are now extensively applied across various …

Psychological measurement is essential for mental health, self-understanding, and personal
development. Traditional methods, such as self-report scales and psychologist interviews …

Decision-making, a complicated task requiring various types of abilities, presents an
excellent framework for assessing Large Language Models (LLMs). Our research …

Recent advancements in large language models (LLMs) have significantly boosted the rise
of Role-Playing Language Agents (RPLAs), ie, specialized AI systems designed to simulate …