[2510.18866] LightMem: Lightweight and Efficient Memory-Augmented Generation

Computer Science > Computation and Language arXiv:2510.18866 (cs) [Submitted on 21 Oct 2025 (v1), last revised 28 Feb 2026 (this version, v4)] Title:LightMem: Lightweight and Efficient Memory-Augmented Generation Authors:Jizhan Fang, Xinle Deng, Haoming Xu, Ziyan Jiang, Yuqi Tang, Ziwen Xu, Shumin Deng, Yunzhi Yao, Mengru Wang, Shuofei Qiao, Huajun Chen, Ningyu Zhang View a PDF of the paper titled LightMem: Lightweight and Efficient Memory-Augmented Generation, by Jizhan Fang and 11 other authors View PDF HTML (experimental) Abstract:Despite their remarkable capabilities, Large Language Models (LLMs) struggle to effectively leverage historical interaction information in dynamic and complex environments. Memory systems enable LLMs to move beyond stateless interactions by introducing persistent information storage, retrieval, and utilization mechanisms. However, existing memory systems often introduce substantial time and computational overhead. To this end, we introduce a new memory system called LightMem, which strikes a balance between the performance and efficiency of memory systems. Inspired by the Atkinson-Shiffrin model of human memory, LightMem organizes memory into three complementary stages. First, cognition-inspired sensory memory rapidly filters irrelevant information through lightweight compression and groups information according to their topics. Next, topic-aware short-term memory consolidates these topic-based groups, organizing and summarizing content for mo...