AI & Machine Learning · Computer Science & AI
Multiagent Systems
The newest papers in Multiagent Systems that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
829 papers, from 4 September 2026 to 5 November 2026: 829 arXiv preprints.
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Embodied Semantic Communication for Collective Autonomous Agents: A Tutorial on Representation, Wireless Delivery, and Closed-Loop Coordination
As autonomous systems and embodied intelligence enter the dynamic physical world, multi-agent collaboration calls for a paradigm shift in communication design.Reasoning with Neural Cellular Automata
Modern AI architectures used to solve visual reasoning tasks typically rely heavily on global connectivity and synchronization.MERID: Multimodal Exploration via Recursive Self-Improvement Agents for Major Depression Analysis
Major depressive disorder (MDD) severely impacts daily activities and quality of life.Fully Decentralized and Safety-Aware Multi-Agent Reinforcement Learning for Control on Networks
This paper develops a safe and fully decentralized multi-agent reinforcement learning (MARL) algorithm to solve a class of discrete-time control problems on networks, including the persistent…ORBIT: A Framework for Multi-Agent Safety and Security Evaluations
Multi-agent LLM systems are increasingly deployed for complex, long-horizon tasks or emerge as a natural consequence of agents interacting in the wild.ParallelPilot: Supporting Coordination and Monitoring in Parallel AI Coding
As coding assistants become increasingly autonomous, developers run multiple sessions in parallel, shifting the challenge from code generation alone to coordinating and monitoring concurrent agent…Modular Discovery of General Game-Playing Algorithms with Large Language Models
General Game Playing across arbitrary games from rules alone remains challenging due to differing algorithmic requirements across game classes and strict decision-time constraints.CORTEX: A Verified Experience Layer for Generalist Agents
An agent can solve a task today and face the same task under new facts, tools, or governing knowledge tomorrow.SIVIA-RSI: Source-Grounded Adaptation of Diagramming Skills
Scientific method diagrams express computations through entities, dependencies, and conditional routes.DataMagic: Authoring Data Videos through Declarative Multi-Agent Orchestration
Data videos communicate data insights through dynamic charts, voice narration, and synchronized animations, and have become a widely adopted form of data storytelling.Raven: The Harness of Harnesses for Composable Agentic Intelligence
As large language models advance, AI agents are moving beyond isolated, domain-specific tasks toward long-horizon, cross-domain workflows.LLMs Trust Their Own: Identity-Dependent Conformity in Multi-Agent Systems
Large language models (LLMs) are increasingly deployed in multi-agent settings, where agents observe and influence one another, making social influence a key dimension of AI behavior and safety.TRACE: Governing Memory Validity in Evolving Multi-Agent Systems
Persistent memory lets language-model agents carry information across long-running collaborations, but leaves a lifecycle question open: what may a returning agent still act on once the shared state…Nearly Group-Separable Elections
We study the problem of computing how close a given election is to being group-separable, measuring proximity by swaps of adjacent candidates in the votes.MA-JEPA: Joint-Embedding World Models for Multi-Agent Reinforcement Learning
World models improve sample efficiency by training policies on imagined trajectories, but their usefulness depends on learning representations that capture the information needed for future control.DEALS: Decentralized Expertise-Aware Load Serving for Multi-Agent LLM Systems
Multi-agent systems (MAS) have recently emerged as an effective approach for coordinating large language model (LLM)-based agents to solve complex tasks through structured interactions.Population Physics, Population Problems: Safety and Emergence in LLM Societies
The collective behaviour of large language model (LLM) societies is not the sum of their individual outputs.Prospective Interpretation Risk: Principled Communication Control Between LLMs
Large language model (LLM) agentic systems increasingly rely on models communicating with one another, yet existing uncertainty and multi-agent methods rarely estimate how a particular receiver will…Maat: Independent Deterministic Contract-Based Governance for Multi-Agent LLM Workflows
Large-language-model multi-agent systems (LLM-MAS) introduce a characteristic reliability problem: an error produced by one agent can be accepted as context by downstream agents and propagate across…Collective Regimes in Multi-Agent LLMs under Reasoning Effort and Communication Topology
Multi-agent LLM systems are increasingly used for deliberation and evaluation, often under the assumption that greater peer interaction leads to more reliable consensus.