11 citations · 12 across the 8 of their papers we have counts for
5 papers · 1 filter
ARCO: Adaptive Rubrics with Co-Evolution for Multi-Step LLM-Based Agents
Zihang Tian, Jingsen Zhang, Rui Li +3
Reinforcement learning for multi-step LLM agents often relies on scalar rewards that indicate success but cannot explain why a trajectory is good or bad. Rubric-based rewards impro…
LLM Agents as Social Scientists: A Human-AI Collaborative Platform for Social Science Automation
Lei Wang, Yuanzi Li, Jinchao Wu +4
Traditional social science research often requires designing complex experiments across vast methodological spaces and depends on real human participants, making it labor-intensive…
Towards Adaptive, Scalable, and Robust Coordination of LLM Agents: A Dynamic Ad-Hoc Networking Perspective
Rui Li, Zeyu Zhang, Xiaohe Bo +4
Multi-agent architectures built on large language models (LLMs) have demonstrated the potential to realize swarm intelligence through well-crafted collaboration. However, the subst…
YuLan-OneSim: Towards the Next Generation of Social Simulator with Large Language Models
Lei Wang, Heyang Gao, Xiaohe Bo +2
Leveraging large language model (LLM) based agents to simulate human social behaviors has recently gained significant attention. In this paper, we introduce a novel social simulato…
A Survey on the Memory Mechanism of Large Language Model based Agents
Zeyu Zhang, Xiaohe Bo, Chen Ma +6
Large language model (LLM) based agents have recently attracted much attention from the research and industry communities. Compared with original LLMs, LLM-based agents are feature…