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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
The paper list of "Memory in the Age of AI Agents: A Survey"
| Date | Stars |
|---|---|
| 2026-07-31 | 2275 |
| 2026-08-02 | 2279 |
| 2026-08-06 | 2279 |
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<!-- # Memory in the Age of AI Agents: A Survey --> <h1 align="center"> <strong>Memory in the Age of AI Agents: A Survey</strong> </h1> <div align="center"> [](https://arxiv.org/abs/2512.13564) [](https://huggingface.co/papers/2512.13564) [](https://github.com/Shichun-Liu/Agent-Memory-Paper-List/pulls) [](https://star-history.com/#Shichun-Liu/Agent-Memory-Paper-List) [](LICENSE) [](https://www.semanticscholar.org/paper/d362b7619fcd2df4241696a19aec95961b8a729c) </div> ## 📢 News - [2026/01/29] 🎉 Our repository has reached **1k stars**! Thank you all for your support and interest in Agent Memory research! - [2026/01/13] 📄 We have updated our survey to incorporate several recent works, and we sincerely thank the community for their valuable contributions and suggestions. See [Memory in the Age of AI Agents: A Survey](https://arxiv.org/abs/2512.13564) for the paper! - [2025/12/16] 🎉 Our paper is featured on [Huggingface Daily Paper #1](https://huggingface.co/papers/date/2025-12-16)! - [2025/12/16] 📚 We create this repository to maintain a paper list on Agent Memory. More papers are coming soon! - [2025/12/16] 📄 Our survey is released! See [Memory in the Age of AI Agents: A Survey](https://arxiv.org/abs/2512.13564) for the paper! <div align="center"> <img src="assets/main.png" alt="Overview of agent memory organized by the unified taxonomy" width="80%" /> <p><em><strong>Figure:</strong> Overview of agent memory organized by the unified taxonomy of <strong>forms</strong>, <strong>functions</strong>, and <strong>dynamics</strong>.</em></p> </div> ## 👋 Introduction Memory serves as the cornerstone of foundation model-based agents, underpinning their ability to perform long-horizon reasoning, adapt continually, and interact effectively with complex environments. Despite the explosion of research in this field, the landscape remains highly fragmented, with loosely defined terminologies and inconsistent taxonomies. This repository aims to bridge this gap. We distinguish Agent Memory from related concepts like RAG and Context Engineering, and provide a comprehensive overview through three unified lenses: - Forms (What Carries Memory?): Categorizing memory by its storage medium—Token-level (explicit & discrete), Parametric (implicit weights), and Latent (hidden states) . - Functions (Why Agents Need Memory?): Moving beyond simple temporal divisions to a functional taxonomy: Factual (knowledge), Experiential (insights & skills), and Working Memory (active context management) . - Dynamics (How Memory Evolves?): Dissecting the operational lifecycle into Formation (extraction), Evolution (consolidation & forgetting), and Retrieval (access strategies) . Through this structure, we hope to provide a conceptual foundation for rethinking memory as a first-class primitive in future agentic intelligence. ## 💡 Concepts <div align="center"> <img src="assets/concept.png" alt="Conceptual Comparison" width="80%" /> <p><em><strong>Figure:</strong> Conceptual comparison of <strong>Agent Memory</strong> with <strong>LLM Memory</strong>, <strong>RAG</strong>, and <strong>Context Engineering</strong>.</em></p> </div> ## 📚 Paper list ### Factual Memory #### Token-level - [2026/01] Memory Matters More:
Excerpt of 33,358 characters
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Yuyang Hu · China
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Allen Schmaltz
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Nicolò Boschi · @vectorize-io · Italy
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Mo Li · Tsinghua University · China
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:1069117b17f5d050, topic:memory
matched fp:1069117b17f5d050, name:paper list, desc:paper list