mlsanityData to 7 Oct 2026

INMS: Memory Sharing for Large Language Model based Agents

arXiv 2404.09982 ↗First posted 15 Apr 2024cs.CLcited by 31

On the map: LLM agents and tool use → Agent memory systems

Abstract (arXiv)

While Large Language Model (LLM) based agents excel at complex tasks, their performance in open-ended scenarios is often constrained by isolated operation and reliance on static databases, missing the dynamic knowledge exchange of human dialogue. To bridge this gap, we propose the INteractive Memory Sharing (INMS) framework, an asynchronous interaction paradigm for multi-agent systems. By integrating real-time memory filtering, storage, and retrieval, INMS establishes a shared conversational memory pool. This enables continuous, dialogue-like memory sharing among agents, promoting collective self-enhancement and dynamically refining the retrieval mediator based on interaction history. Extensive experiments across three datasets demonstrate that INMS improves agent performance by effectively modeling multi-agent interaction and collective knowledge sharing.

Key facts. Cited by 31 papers in the map (data through 7 Oct 2026). Placed in Agent memory systems, one of 16 directions in LLM agents and tool use. Builds on 34 of its 57 references that are in the map. First posted on arXiv 15 Apr 2024.

Builds on

34 of 57 references.

References · 34

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  3. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  4. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  5. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,462
  6. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,500
  7. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,222
  8. 2021SimCSE: Simple Contrastive Learning of Sentence Embeddingscited by 2,168
  9. 2023Voyager: An Open-Ended Embodied Agent with Large Language Modelscited by 2,081
  10. 2023MemGPT: Towards LLMs as Operating Systemscited by 1,295
  11. 2021Unsupervised Dense Information Retrieval with Contrastive Learningcited by 1,203
  12. 2021What Makes Good In-Context Examples for GPT-3?cited by 1,184
22 more
  1. 2022Large Language Models Are Human-Level Prompt Engineerscited by 1,020
  2. 2022Atlas: Few-shot Learning with Retrieval Augmented Language Modelscited by 940
  3. 2023REPLUG: Retrieval-Augmented Black-Box Language Modelscited by 786
  4. 2021Cross-Task Generalization via Natural Language Crowdsourcing Instructionscited by 696
  5. 2023In-Context Retrieval-Augmented Language Modelscited by 694
  6. 2021Learning To Retrieve Prompts for In-Context Learningcited by 641
  7. 2022PAL: Program-aided Language Modelscited by 635
  8. 2023A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPTcited by 612
  9. 2023Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memorycited by 288
  10. 2021AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Promptscited by 265
  11. 2022Can language models learn from explanations in context?cited by 248
  12. 2021Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Samplingcited by 238
  13. 2020Generation-Augmented Retrieval for Open-domain Question Answeringcited by 186
  14. 2023Synapse: Trajectory-as-Exemplar Prompting with Memory for Computer Controlcited by 180
  15. 2022Few-shot training LLMs for project-specific code-summarizationcited by 128
  16. 2021Reframing Human-AI Collaboration for Generating Free-Text Explanationscited by 125
  17. 2023Solving Math Word Problems by Combining Language Models With Symbolic Solverscited by 124
  18. 2023MemoChat: Tuning LLMs to Use Memos for Consistent Long-Range Open-Domain Conversationcited by 94
  19. 2023Dr.ICL: Demonstration-Retrieved In-context Learningcited by 71
  20. 2023Think-in-Memory: Recalling and Post-thinking Enable LLMs with Long-Term Memorycited by 64
  21. 2023Learning to Retrieve In-Context Examples for Large Language Modelscited by 60
  22. 2021The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Designcited by 33

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 4; 2025: 14; 2026: 13.

31 papers.

Sort:

By area:

  1. 2025Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Modelscited by 291
  2. 2025Memory in the Age of AI Agentscited by 285
  3. 2025Memory Injection Attacks on LLM Agents via Query-Only Interactioncited by 127
  4. 2025Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systemscited by 125
  5. 2025A Survey of Context Engineering for Large Language Modelscited by 120
  6. 2025Collaborative Memory: Multi-User Memory Sharing in LLM Agents with Dynamic Access Controlcited by 56
  7. 2025A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasurescited by 54
  8. 2026A Survey of Agentic Reasoning for Large Language Models: Towards Recursively Self-Improving and Collective Agentscited by 47
  9. 2024Richelieu: Self-Evolving LLM-Based Agents for AI Diplomacycited by 36
  10. 2025OSC: Cognitive Orchestration through Dynamic Knowledge Alignment in Multi-Agent LLM Collaborationcited by 29
  11. 2025MAGPIE: A benchmark for Multi-AGent contextual PrIvacy Evaluationcited by 27
  12. 2025R3Mem: Bridging Memory Retention and Retrieval via Reversible Compressioncited by 12
19 more
  1. 2025AI Meets Brain: Memory Systems from Cognitive Neuroscience to Autonomous Agentscited by 12
  2. 2026Toward Efficient Agents: Memory, Tool learning, and Planningcited by 11
  3. 2025VLM Can Be a Good Assistant: Enhancing Embodied Visual Tracking with Self-Improving Vision-Language Modelscited by 7
  4. 2026MAP-Graph: Provenance-Aware Shared Memory for Multi-Agent Workflowscited by 7
  5. 2024A Taxonomy of Architecture Options for Foundation Model-based Agents: Analysis and Decision Modelcited by 4
  6. 2025The Society of HiveMind: Multi-Agent Optimization of Foundation Model Swarms to Unlock the Potential of Collective Intelligencecited by 4
  7. 2026State Contamination in Memory-Augmented LLM Agentscited by 4
  8. 2024BMW Agents -- A Framework For Task Automation Through Multi-Agent Collaborationcited by 3
  9. 2024Task-Aligned Tool Recommendation for Large Language Modelscited by 3
  10. 2026Individual Turing Test: A Case Study of LLM-based Simulation Using Longitudinal Personal Datacited by 1
  11. 2026When Does Memory Help Multi-Trajectory Inference for Tool-Use LLM Agents?cited by 1
  12. 2026Scalable Behaviour Cloning on Browser Using via Skill Distillationcited by 1
  13. 2026Multi-Agent Agentic Graph Learning via Structural Signaturescited by 1
  14. 2025From Capabilities to Performance: Evaluating Key Functional Properties of LLM Architectures in Penetration Testingcited by 0
  15. 2026Scene-Aware Memory Discrimination: Deciding Which Personal Knowledge Stayscited by 0
  16. 2026Revolutionizing Long-Term Memory in AI: New Horizons with High-Capacity and High-Speed Storagecited by 0
  17. 2026Collaborative Memory for Multi-Agent VLM Systemscited by 0
  18. 2026Learning from Others, Acting for You: Cross-User Memory Sharing for LLM Agentscited by 0
  19. 2026Federated Agent Optimizationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Memory in the LLM Era: Modular Architectures and Strategies in a Unified Framework
  2. 2026AMA: Adaptive Memory via Multi-Agent Collaboration
  3. 2026AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applications
  4. 2025G-Memory: Tracing Hierarchical Memory for Multi-Agent Systems
  5. 2026MemCo: Memory-Centric Collaboration for Generalizing LLM Agents to Unseen Environments
  6. 2024On the Structural Memory of LLM Agents
  7. 2025Intrinsic Memory Agents: Heterogeneous Multi-Agent LLM Systems through Structured Contextual Memory
  8. 2026Memory for Autonomous LLM Agents:Mechanisms, Evaluation, and Emerging Frontiers