15 citations · 24 across the 9 of their papers we have counts for
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cs.AI2025
RMoA: Optimizing Mixture-of-Agents through Diversity Maximization and Residual Compensation
Zhentao Xie, Chengcheng Han, Jinxin Shi +4
Although multi-agent systems based on large language models show strong capabilities on multiple tasks, they are still limited by high computational overhead, information loss, and…
cs.AI2025★ 15 cited
A Survey on the Optimization of Large Language Model-based Agents
Shangheng Du, Jiabao Zhao, Jinxin Shi +4
With the rapid development of Large Language Models (LLMs), LLM-based agents have been widely adopted in various fields, becoming essential for autonomous decision-making and inter…
cs.AI2023★ 6 cited
CGMI: Configurable General Multi-Agent Interaction Framework
Shi Jinxin, Zhao Jiabao, Wang Yilei +3
Benefiting from the powerful capabilities of large language models (LLMs), agents based on LLMs have shown the potential to address domain-specific tasks and emulate human behavior…