# Paper: Exploring Cross-Scenario Generality of Agentic Memory Systems: Diagnostics and a Strong Baseline

---
type: paper
title: "Exploring Cross-Scenario Generality of Agentic Memory Systems: Diagnostics and a Strong Baseline"
authors: Zhikai Chen, Jialiang Gu, Junyu Yin, Xianxuan Long, Shenglai Zeng, Xiaoze Liu, Kai Guo, Keren Zhou, et al.
year: 2026
venue: arXiv
url: https://arxiv.org/abs/2606.04315
code_url:
source: arxiv
collected_at: 2026-07-08
published_at: 2026-06-03
updated_at: 2026-06-03
status: skimmed
relevance: high
topics:
  - agent-evaluation
  - memory
  - planning
  - rag
  - tool-use
methods:
  - agentic-memory-harness
  - schema-diagnostics
  - active-retrieval
benchmarks:
  - LoCoMo
  - HotpotQA
  - AMABench
  - ALFWorld
models:
  -
datasets:
  - cs.AI
related_concepts:
  - schema-commitment
  - agentic-retrieval
related_jobs:
  -
related_experiments:
  - KC-001-agent-memory-pilot
related_projects:
  - learning/agent-memory
collection_score: 19
collection_queries: agent-memory
---

## One-line Takeaway

复杂索引会在写入时承诺 schema；保留原始证据并让 Agent 按问题主动读取，往往有更好的跨场景通用性。

## Pilot Skim

- problem: 为单一场景设计的 memory 在对话、QA、trajectory 和动态任务之间难以泛化。
- method: 诊断 representation loss 和 retrieval loss，并提出带主动工具循环的 AutoMEM。
- evidence: AutoMEM 在 LoCoMo 为 67.3，对 long context 的 61.5；ALFWorld 诊断显示 golden procedure 仍低于训练后的 actor。
- boundary: agentic harness 不是每个场景最省 token；动态任务上限可能在 policy 而非 memory。

## Used In

- [Agent Memory evidence matrix](../../learning/agent-memory/evidence-matrix.md)

## Links

- arXiv: https://arxiv.org/abs/2606.04315