# "My agent understands me better": Integrating Dynamic Human-like Memory Recall and Consolidation in LLM-Based Agents arXiv: https://arxiv.org/abs/2404.00573 ยท HTML: https://mlsanity.com/paper/2404.00573/ ## Key facts - Cited by 29 papers in the map (data through 14 Oct 2026). - Placed in Agent memory systems, one of 16 directions in LLM agents and tool use. - Builds on 5 of its 32 references that are in the map. - First posted on arXiv 31 Mar 2024. ## Placed in - LLM agents and tool use / [Agent memory systems](https://mlsanity.com/agents/agent-memory-systems/) ## Builds on (most cited first, 5 of 5) - [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023) - [Transformer Feed-Forward Layers Are Key-Value Memories](https://mlsanity.com/paper/2012.14913/) (2020) - [How to Fine-Tune BERT for Text Classification?](https://mlsanity.com/paper/1905.05583/) (2019) - [A Machine With Human-Like Memory Systems](https://mlsanity.com/paper/2204.01611/) (2022) - [Performance Comparison of Large Language Models on VNHSGE English Dataset: OpenAI ChatGPT, Microsoft Bing Chat, and Google Bard](https://mlsanity.com/paper/2307.02288/) (2023) ## Built on by (most cited first, 29 of 29) - [AI Agents Under Threat: A Survey of Key Security Challenges and Future Pathways](https://mlsanity.com/paper/2406.02630/) (2024) - [Memp: Exploring Agent Procedural Memory](https://mlsanity.com/paper/2508.06433/) (2025) - [How Memory Management Impacts LLM Agents: An Empirical Study of Experience-Following Behavior](https://mlsanity.com/paper/2505.16067/) (2025) - [MemInsight: Autonomous Memory Augmentation for LLM Agents](https://mlsanity.com/paper/2503.21760/) (2025) - [AgentArmor: Enforcing Program Analysis on Agent Runtime Trace to Defend Against Prompt Injection](https://mlsanity.com/paper/2508.01249/) (2025) - [Richelieu: Self-Evolving LLM-Based Agents for AI Diplomacy](https://mlsanity.com/paper/2407.06813/) (2024) - [A Survey on Medical Large Language Models: Technology, Application, Trustworthiness, and Future Directions](https://mlsanity.com/paper/2406.03712/) (2024) - [Graph-based Agent Memory: Taxonomy, Techniques, and Applications](https://mlsanity.com/paper/2602.05665/) (2026) - [MADial-Bench: Towards Real-world Evaluation of Memory-Augmented Dialogue Generation](https://mlsanity.com/paper/2409.15240/) (2024) - [ELLMA-T: an Embodied LLM-agent for Supporting English Language Learning in Social VR](https://mlsanity.com/paper/2410.02406/) (2024) - [SynapticRAG: Enhancing Temporal Memory Retrieval in Large Language Models through Synaptic Mechanisms](https://mlsanity.com/paper/2410.13553/) (2024) - [Generative AI for Self-Adaptive Systems: State of the Art and Research Roadmap](https://mlsanity.com/paper/2512.04680/) (2025) - [Navigating the Unknown: A Chat-Based Collaborative Interface for Personalized Exploratory Tasks](https://mlsanity.com/paper/2410.24032/) (2024) - [UserCentrix: An Agentic Memory-augmented AI Framework for Smart Spaces](https://mlsanity.com/paper/2505.00472/) (2025) - [Towards Pervasive Distributed Agentic Generative AI -- A State of The Art](https://mlsanity.com/paper/2506.13324/) (2025) - [Semantic Commit: Helping Users Update Intent Specifications for AI Memory at Scale](https://mlsanity.com/paper/2504.09283/) (2025) - [MARK: Memory Augmented Refinement of Knowledge](https://mlsanity.com/paper/2505.05177/) (2025) - [Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph](https://mlsanity.com/paper/2506.08098/) (2025) - [Evolution in Simulation: AI-Agent School with Dual Memory for High-Fidelity Educational Dynamics](https://mlsanity.com/paper/2510.11290/) (2025) - [Does My Chatbot Have an Agenda? Understanding Human and AI Agency in Human-Human-like Chatbot Interaction](https://mlsanity.com/paper/2601.22452/) (2026) - [ACAI for SBOs: AI Co-creation for Advertising and Inspiration for Small Business Owners](https://mlsanity.com/paper/2503.06729/) (2025) - [Static Sandboxes Are Inadequate: Modeling Societal Complexity Requires Open-Ended Co-Evolution in LLM-Based Multi-Agent Simulations](https://mlsanity.com/paper/2510.13982/) (2025) - [Beyond Training: Enabling Self-Evolution of Agents with MOBIMEM](https://mlsanity.com/paper/2512.15784/) (2025) - [AI and My Values: User Perceptions of LLMs' Ability to Extract, Embody, and Explain Human Values from Casual Conversations](https://mlsanity.com/paper/2601.22440/) (2026) - [MineNPC-Task: Task Suite for Memory-Aware Minecraft Agents](https://mlsanity.com/paper/2601.05215/) (2026) - [C-TRAIL: A Commonsense World Framework for Trajectory Planning in Autonomous Driving](https://mlsanity.com/paper/2603.29908/) (2026) - [ChronoMem: Version Control and Semantic Rollback for Large Language Model Agent Memory](https://mlsanity.com/paper/2607.27773/) (2026) - [SNAP: A Plan-Driven Framework for Controllable Interactive Narrative Generation](https://mlsanity.com/paper/2601.11529/) (2025) - [MAPS: Modeling Co-Existing Subjective Perspectives and Shared Meaning in Multi-Agent Cognitive Dialogue](https://mlsanity.com/paper/2607.14110/) (2026) ## Abstract (arXiv) In this study, we propose a novel human-like memory architecture designed for enhancing the cognitive abilities of large language model based dialogue agents. Our proposed architecture enables agents to autonomously recall memories necessary for response generation, effectively addressing a limitation in the temporal cognition of LLMs. We adopt the human memory cue recall as a trigger for accurate and efficient memory recall. Moreover, we developed a mathematical model that dynamically quantifies memory consolidation, considering factors such as contextual relevance, elapsed time, and recall frequency. The agent stores memories retrieved from the user's interaction history in a database that encapsulates each memory's content and temporal context. Thus, this strategic storage allows agents to recall specific memories and understand their significance to the user in a temporal context, similar to how humans recognize and recall past experiences.