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55 papers match

cs.MA2026

-Mem: An Online Reliability Memory for LLM-based Multi-Agent Systems

Peilin Feng, Suorong Yang, Soujanya Poria

The paper introduces Σ‑Mem, an online memory system that tracks and updates reliability evidence for individual agents and their relationships in large language model multi‑agent s…

#large language models#multi-agent systems#reliability assessment#online memory
cs.MA2026

Scaling LLM-Driven Multi-Agent Systems: Design Principles and Architectural Scalability Analysis

Linus Sander, Fengjunjie Pan, Vahid Zolfaghari +3

The paper identifies four design principles for building scalable large‑language‑model‑driven multi‑agent systems, proposes a reference architecture based on a constrained directed…

#large language models#multi-agent systems#scalability#system architecture
cs.AI2026

SKIMIX: Multi-Agent Harness-Time Scaling with Skill Mixture for Dynamic Harness Engineering

Jia Luo

The paper introduces SKIMIX, a multi-agent framework that enables AI agents to retrieve, combine, and evolve skills from a large library using embedding-based retrieval and submodu…

#multi-agent systems#skill retrieval#skill composition#reasoning benchmarks
cs.AI2026

MANTA: Multi-Agent Network Topology Adaptation for Self-Evolving Multi-Agent Systems

Mao-xun Huang, Jerry Wang, Yi-Cheng Lai +3

The paper presents MANTA, a framework that lets large language model‑driven multi‑agent systems dynamically adjust their communication topology during inference, updating roles, li…

#multi-agent systems#network topology adaptation#large language models#dynamic collaboration
cs.MA2026

Argonaut: Interactive Visual Exploration for Distributed Optimization

Srijoni Majumdar, Chuhao Qin, Evangelos Pournaras

Argonaut is a lightweight, containerized dashboard that lets users interactively visualize and explore the entire search process of distributed multi‑agent discrete‑choice optimiza…

#distributed optimization#multi-agent systems#visual analytics#human-in-the-loop
cs.AI2026

UrbanDS: A Graph-Guided LLM Multi-Agent System for Data-Intensive Urban Tasks

Zhilun Zhou, Jianghao Yu, Yuming Lin +4

The paper presents UrbanDS, a graph-guided multi-agent system that uses large language models to organize heterogeneous urban datasets in a unified graph and coordinate specialized…

#urban data analysis#graph-based dataset management#llm agents#multi-agent systems