---
title: "MemLens：面向LLM智能体的价值感知记忆管理系统及交互分析平台"
source: "arXiv AI/CL/LG（论文）"
source_tier: "t2"
url: "https://arxiv.org/abs/2607.25992v1"
permalink: "https://feed.astralor.com/items/itm_f6bd977e16fa6e30d48a5397"
published: "2026-07-28T17:08:56.000Z"
score: 74
channel: "ai"
tags: ["LLM智能体","MemLens","Shapley值","交互式分析","记忆管理"]
---

# MemLens：面向LLM智能体的价值感知记忆管理系统及交互分析平台

## AI 点评

> 这篇论文对从事LLM Agent开发的团队和研究者非常值得关注——它直接解决了长期记忆管理中‘该存什么、该扔什么’的核心问题。Shapley值的引入既降低了遗忘带来的信息丢失风险，又避免了存储膨胀。交互式面板的设计让调试变得直观，特别适合需要持续优化记忆策略的产品工程师。

## 速览

MemLens 提出一种价值感知的记忆管理方法，将异构交互记录作为一等数据对象，通过 Shapley 值评估记忆效用、分层可视化存储结构，并支持多种策略对比（响应质量、检索延迟、Token消耗）。系统提供端到端交互式仪表盘，使研究者与开发者能直观理解并优化 LLM 智能体的长期记忆，提升推理个性化与知识复用效率。实验基于 study-copilot 应用验证了其在减少冗余、提升响应质量上的有效性。

## 关键点

- 提出将记忆记录作为一等数据对象，采用 Shapley 值进行效用评估，实现价值感知存储
- 构建端到端交互式分析仪表盘，支持记忆值可视化、层级结构浏览与管理策略对比
- 在 study-copilot 应用场景中验证了系统在减少冗余记录、提升响应质量与检索效率方面的优势

## 全文

Recently, memory management has become a key infrastructure for LLM-based agents, as it directly affects long-horizon reasoning, personalized responses, and knowledge reuse. However, existing LLM memory systems typically adopt a coarse-grained (utility-agnostic) manner that treats heterogeneous user-LLM interaction records uniformly, leading to redundant and low-impact records persisting in the memory repository. To address this challenge, we present MemLens, a value-aware memory management system that takes memory records as first-class data objects. MemLens provides an end-to-end interactive analytics dashboard that exposes the complete memory lifecycle, including Shapley-style memory evaluation, value-aware storage, and memory-assisted response. Through a study-copilot application, the system enables users to inspect memory values, visualize hierarchical memory structures, and compare various memory management strategies in terms of response quality, retrieval latency, and token consumption. Therefore, our MemLens can serve as an efficient, interpretable, and personalized long-term memory management system for LLM-based agents.

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引用前请核对原文;本文由星际流动整理:https://feed.astralor.com/items/itm_f6bd977e16fa6e30d48a5397