wuyang
63 lines
1.8 KiB
Markdown
63 lines
1.8 KiB
Markdown
# Paper: Remember the Decision, Not the Description: A Rate-Distortion Framework for Agent Memory
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---
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type: paper
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title: "Remember the Decision, Not the Description: A Rate-Distortion Framework for Agent Memory"
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authors: Mingxi Zou, Zhihan Guo, Langzhang Liang, Zhuo Wang, Qifan Wang, Qingsong Wen, Irwin King, Lizhen Qu, et al.
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year: 2026
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venue: arXiv
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url: https://arxiv.org/abs/2605.10870
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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: 2026-05-11
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updated_at: 2026-05-11
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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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methods:
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- decision-rate-distortion
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- k-slot-memory
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- certified-memory-split
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benchmarks:
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- LoCoMo
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- synthetic-decision-diagnostics
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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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- decision-sufficient-state
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- selective-forgetting
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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: 13
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collection_queries: language-agent
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---
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## One-line Takeaway
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Memory 应保留会改变决策的历史差异，而不是优先保留描述最相似或最完整的记录。
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## Pilot Skim
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- problem: relevance、salience 和 summary fidelity 没有直接刻画 memory 对未来决策的价值。
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- method: 在 K 个 runtime state 预算下定义 decision distortion、forgetting boundary，并按 certified conflict 拆分 state。
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- evidence: LoCoMo 子集上描述相似度与 evidence compatibility 的相关仅 0.103；matched budget 下 DeMem gold evidence recall 为 83%，描述检索为 66%。
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- boundary: 理论主要在 contextual bandit 和有限状态设定中建立，实际 LLM 冲突判定仍依赖 judge 与近似算法。
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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/2605.10870
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