Agentsensus: Consensus-Compressed Shared Memory for Multi-Agent Story Worlds

arXiv:2609.32297 · cs.AI, cs.CL, cs.MA · Submitted 2026-09-26 · Read on arXiv

cs.AI, cs.CL, cs.MA

Submitted: 2026-09-26

Updated: 2026-09-26

Terminology

• Grounding — 6× in this paper · explained in 3 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Actor — 3× in this paper · explained in 3 episodes
• Multi-Agent System — 3× in this paper · explained in 6 episodes
• Agent Memory — 2× in this paper · explained in 1 episode
• Meeting of the Association for Computational Linguistics — 2× in this paper
• RAG — 2× in this paper · explained in 3 episodes
• Redundancy — 2× in this paper · explained in 2 episodes
• Empirical Methods in Natural Language Processing — 1× in this paper
• LLM judge — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• SemDeDup: Data-efficient learning at web-scale through semantic deduplication
• From Local to Global: A Graph RAG Approach to Query-Focused Summarization
• HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models
• MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework
• War and Peace (WarAgent): Large Language Model-based Multi-Agent Simulation of World Wars
• Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
• CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society
• Co-Writing Screenplays and Theatre Scripts with Language Models: An Evaluation by Industry Professionals
• MemGPT: Towards LLMs as Operating Systems
• Generative Agents: Interactive Simulacra of Human Behavior
• LLM Agents Grounded in Self-Reports Enable General-Purpose Simulation of Individuals
• ChatDev: Communicative Agents for Software Development
• BookWorld: From Novels to Interactive Agent Societies for Creative Story Generation
• Collaborative Memory: Multi-User Memory Sharing in LLM Agents with Dynamic Access Control
• Character-LLM: A Trainable Agent for Role-Playing
• Reflexion: Language Agents with Verbal Reinforcement Learning
• AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation
• A-MEM: Agentic Memory for LLM Agents
• Re3: Generating Longer Stories With Recursive Reprompting and Revision
• DOC: Improving Long Story Coherence With Detailed Outline Control

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