5 papers
IF-MAP: Influence-Function-Inspired Agent Prioritization in Multi-Agent Systems
Jie Mao, Pingchen Lu, Zikun Qu +6
Improving every agent in an LLM-based multi-agent system can be prohibitively costly, making it important to identify which agent should be prioritized to achieve the greatest syst…
Fusion is the New Mutation: Bandit-Guided Evolution on Workflow Graphs
Zhiwei Shang, Jiahang Sun, Mingrong Gong +9
Automated agentic workflow optimization relies on costly evaluations, making it essential to allocate a limited evaluation budget effectively. Multi-parent fusion can reuse designs…
MASPOB: Bandit-Based Prompt Optimization for Multi-Agent Systems with Graph Neural Networks
Zhi Hong, Qian Zhang, Jiahang Sun +5
Large Language Models (LLMs) have achieved great success in many real-world applications, especially the one serving as the cognitive backbone of Multi-Agent Systems (MAS) to orche…
Online Clustering of Dueling Bandits
Zhiyong Wang, Jiahang Sun, Mingze Kong +4
The contextual multi-armed bandit (MAB) is a widely used framework for problems requiring sequential decision-making under uncertainty, such as recommendation systems. In applicati…
Large Language Model-Enhanced Multi-Armed Bandits
Jiahang Sun, Zhiyong Wang, Runhan Yang +3
Large language models (LLMs) have been adopted to solve sequential decision-making tasks such as multi-armed bandits (MAB), in which an LLM is directly instructed to select the arm…