arXiv AI By Dac Duy Anh Nguyen, Zhangchi Qiu, Shigeng Chen, Alan Wee-Chung Liew

Graph-Based Personalized Memory for LLM Agents: Representation, Evolution, Retrieval, and Evaluation

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arXiv AI
Jun 9

MemToolAgent overview with a simple restaurant booking scenario where the agent retrieves similar memories, receives feedback on an invalid time format, and generates a reflection to update its memory

arXiv:2606. 07909v1 Announce Type: new Abstract: Modern large language model (LLM) agents can use external tools to help users solve complex tasks.

By Suleyman Armagan Er, Danilo Ribeiro, Yogesh Virkar, Surafel Lakew, Adi Kalyanpur, James Gung, Thomas Delteil, Arshit Gupta
arXiv Computation and Language
3d ago

AtomMem: Building Simple and Effective Memory System for LLM Agents via Atomic Facts

AtomMem is a long‑term memory system for large language models that stores high‑value atomic facts extracted from long‑form interactions. It organizes these facts into hierarchical event structures and temporal profiles, enabling coherent episodic context and dynamic tracking of user attributes. During retrieval, an associative memory graph connects fragmented memories, and experiments on the LoCoMo benchmark show state‑of‑the‑art performance across reasoning tasks.

By Yanyu Yao, Shangze Li, Zhi Zheng, Hui Zheng, Qi Liu, Tong Xu, Enhong Chen