# LiCoMemory: Lightweight and Cognitive Agentic Memory for Efficient Long-Term Reasoning

Source: [LiCoMemory: Lightweight and Cognitive Agentic Memory for Efficient Long-Term Reasoning](<https://www.sota2.com/research/paper/690988863ef7ccd74e5e5c5d>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-01-08T05:00:05.049Z

Authors: Zhengjun Huang, Zhoujin Tian, Qintian Guo, Fangyuan Zhang, Yingli Zhou, Di Jiang, Zeying Xie, Xiaofang Zhou

Published: 2025-11-03T11:02:40.000Z

## Abstract

Large Language Model (LLM) agents exhibit remarkable conversational and reasoning capabilities but remain constrained by limited context windows and the lack of persistent memory. Recent efforts address these limitations via external memory architectures, often employing graph-based representations, yet most adopt flat, entangled structures that intertwine semantics with topology, leading to redundant representations, unstructured retrieval, and degraded efficiency and accuracy. To resolve these issues, we propose LiCoMemory, an end-to-end agentic memory framework for real-time updating and retrieval, which introduces CogniGraph, a lightweight hierarchical graph that utilizes entities and relations as semantic indexing layers, and employs temporal and hierarchy-aware search with integrated reranking for adaptive and coherent knowledge retrieval. Experiments on long-term dialogue benchmarks, LoCoMo and LongMemEval, show that LiCoMemory not only outperforms established baselines in temporal reasoning, multi-session consistency, and retrieval efficiency, but also notably reduces update latency. Our official code and data are available at https://github.com/EverM0re/LiCoMemory.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Long-term dialogue memory on LongMemEval (test)](<https://www.sota2.com/research/sota/long-term-dialogue-memory-on-longmemeval-test.md>): Long-term dialogue memory; LongMemEval (test); Accuracy: 73.

- [Implicit-conflict resolution on STALE 1.0 (full)](<https://www.sota2.com/research/sota/implicit-conflict-resolution-on-stale-1-0-full.md>): Implicit-conflict resolution; STALE 1.0 (full); Type I SR Accuracy: 15.5.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2511.01448>)

[PDF](<https://arxiv.org/pdf/2511.01448.pdf>)