AgentRoom: Concurrent Multi-Agent Coding in a CRDT-Backed Shared Workspace

arXiv:2608.23740 · cs.AI, cs.SE · Submitted 2026-08-24 · Read on arXiv

cs.AI, cs.SE

Submitted: 2026-08-24

Updated: 2026-08-24

Code: https://github.com/yjs/yjs

Terminology

• Ablation — 19× in this paper · explained in 1 episode
• Consistency — 7× in this paper · explained in 3 episodes
• Robustness — 7× in this paper · explained in 5 episodes
• Homogeneity — 3× in this paper · explained in 2 episodes
• Scaffolding — 3× in this paper · explained in 3 episodes
• Cooperation — 2× in this paper · explained in 2 episodes
• LLM-as-a-Judge — 2× in this paper · explained in 3 episodes
• Multi-agent Collaboration — 2× in this paper · explained in 2 episodes
• Self-consistency — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Affordance — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Model Context Protocol — 1× in this paper
• Model Context Protocol (MCP) — 1× in this paper · explained in 8 episodes
• Multi-Agent Framework — 1× in this paper · explained in 3 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes

Sources

• Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency
• AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors
• MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework
• AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation
• CODESIM: Multi-Agent Code Generation and Problem Solving through Simulation-Driven Planning and Debugging
• A Conflict-Free Replicated JSON Datatype
• Prompting Large Language Models to Tackle the Full Software Development Lifecycle: A Case Study
• Preference Leakage: A Contamination Problem in LLM-as-a-judge
• AgileCoder: Dynamic Collaborative Agents for Software Development based on Agile Methodology
• CodeCoR: An LLM-Based Self-Reflective Multi-Agent Framework for Code Generation
• Generative Agents: Interactive Simulacra of Human Behavior
• SEMAG: Self-Evolutionary Multi-Agent Code Generation
• CodeCRDT: Observation-Driven Coordination for Multi-Agent LLM Code Generation
• Reflexion: Language Agents with Verbal Reinforcement Learning
• Mixture-of-Agents Enhances Large Language Model Capabilities
• OpenHands: An Open Platform for AI Software Developers as Generalist Agents
• Self-Consistency Improves Chain of Thought Reasoning in Language Models
• Self-Preference Bias in LLM-as-a-Judge
• AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems
• VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection