Agentic Context Management: Solving Agent Memory and Cost by Treating Them as Lifecycle and Architecture Problems
- 类型：arxiv
- 标识：2607.21503
- 链接：https://arxiv.org/abs/2607.21503
- 主分类：agent
- 形态：method
- 被引：0
- 被引来源：Semantic Scholar + OpenAlex
- S2被引：0
- OpenAlex被引：0
- 影响力被引：0
- TLDR：The economic case is made: naive context accumulation grows token cost quadratically in conversation length, crude summarization buys linear cost at the price of an accuracy cliff, and only validated compaction achieves linear cost with preserved fidelity.
- OpenAlex ID：W7170546313
- OpenAlex DOI：10.48550/arxiv.2607.21503
- DOI：10.48550/arxiv.2607.21503
- DOI来源：OpenAlex
- 开放获取：green
- 开放获取链接：https://doi.org/10.48550/arxiv.2607.21503
- OpenAlex更新：2026-08-24
- 待LLM分类：否
- 标题中文：Agentic 上下文管理：通过将 Agent 记忆与成本视为生命周期与架构问题来解决
- TLDR中文：论证了经济层面的依据：天真的上下文累积会使 token 成本随对话长度呈二次增长，粗糙的摘要以线性成本换取准确率的断崖式下降，唯有经过验证的压缩才能以线性成本保持保真度。
- 来源文件：
- /inbox/tom/_candidates/2026-07-24-agent-rag-longcontext-candidates.json
- /inbox/tom/_candidates/2026-07-25-agent-rag-longcontext-candidates.json
- /inbox/tom/_candidates/2026-07-26-agent-rag-longcontext-candidates.json
- /inbox/tom/_candidates/2026-07-27-agent-rag-longcontext-candidates.json
- /inbox/tom/_candidates/2026-07-28-agent-rag-longcontext-candidates.json
- /inbox/tom/_candidates/2026-07-28-rag-retrieval-reranking-candidates.json
- [S2 enrich]
- [OpenAlex backfill]