Topology Learning | Yiqiao Jin CS PhD @ Georgia Techhttps://ahren09.github.io/tags/topology-learning/Topology LearningHugo Blox Builder (https://hugoblox.com)en-usFri, 04 Jul 2025 00:00:00 +0000https://ahren09.github.io/media/icon_hu_eee6347cbdb2cc3f.pngTopology Learninghttps://ahren09.github.io/tags/topology-learning/Topological Structure Learning Should Be A Research Priority for LLM-Based Multi-Agent Systemshttps://ahren09.github.io/publication/acl2026_topoagent/Fri, 04 Jul 2025 00:00:00 +0000https://ahren09.github.io/publication/acl2026_topoagent/<h2 id="abstract">Abstract</h2> <p>Large Language Model-based Multi-Agent Systems (MASs) have emerged as a powerful paradigm for tackling complex tasks through collaborative intelligence. Nevertheless, the question of how agents should be structurally organized for optimal cooperation remains largely unexplored. In this position paper, we aim to gently redirect the focus of the MAS research community toward this critical dimension: develop topology-aware MASs for specific tasks. The system consists of three core components — agents, communication links, and communication patterns — that collectively shape its coordination performance and efficiency. We introduce a systematic three-stage framework: agent selection, structure profiling, and topology synthesis.</p> <h2 id="links">Links</h2> <ul> <li> </li> </ul>