wuyang
67 lines
1.8 KiB
Markdown
67 lines
1.8 KiB
Markdown
# Paper: Exploring Cross-Scenario Generality of Agentic Memory Systems: Diagnostics and a Strong Baseline
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---
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type: paper
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title: "Exploring Cross-Scenario Generality of Agentic Memory Systems: Diagnostics and a Strong Baseline"
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authors: Zhikai Chen, Jialiang Gu, Junyu Yin, Xianxuan Long, Shenglai Zeng, Xiaoze Liu, Kai Guo, Keren Zhou, et al.
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year: 2026
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venue: arXiv
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url: https://arxiv.org/abs/2606.04315
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code_url:
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source: arxiv
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collected_at: 2026-07-08
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published_at: 2026-06-03
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updated_at: 2026-06-03
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status: skimmed
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relevance: high
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topics:
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- agent-evaluation
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- memory
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- planning
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- rag
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- tool-use
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methods:
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- agentic-memory-harness
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- schema-diagnostics
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- active-retrieval
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benchmarks:
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- LoCoMo
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- HotpotQA
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- AMABench
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- ALFWorld
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models:
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-
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datasets:
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- cs.AI
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related_concepts:
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- schema-commitment
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- agentic-retrieval
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related_jobs:
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-
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related_experiments:
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- KC-001-agent-memory-pilot
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related_projects:
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- learning/agent-memory
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collection_score: 19
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collection_queries: agent-memory
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---
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## One-line Takeaway
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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。
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## Pilot Skim
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- 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。
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- method: 诊断 representation loss 和 retrieval loss，并提出带主动工具循环的 AutoMEM。
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- 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。
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- 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。
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## Used In
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- [Agent Memory evidence matrix](../../learning/agent-memory/evidence-matrix.md)
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## Links
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- arXiv: https://arxiv.org/abs/2606.04315
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