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arXiv cs.AI· Yubo Ruan, Tao Peng, Jiao Zhang, Chuanguo Ma, Lei Xu, Han Zhou, Wenwu Wang, Xiafei Lv, Xingjie Zhou, Guiju Fan, Hao Wang, Fenghui Zhang, Mao Miao, Shuo Li·· 1 小时前AI 评分52

Folio:面向长时程语言智能体的可恢复多分辨率上下文折叠方法

Folio: Recoverable Multi-Resolution Context Folding for Long-Horizon Language Agents

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论文提出 Folio 上下文管理器,用 L1 回合笔记、L2 事件清单、L3 源记录三层句柄记录、折叠并恢复历史,替代模型摘要式压缩。

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Authors:Yubo Ruan, Tao Peng, Jiao Zhang, Chuanguo Ma, Lei Xu, Han Zhou, Wenwu Wang, Xiafei Lv, Xingjie Zhou, Guiju Fan, Hao Wang, Fenghui Zhang, Mao Miao, Shuo Li

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Abstract:Long-horizon language agents accumulate tool results and replies until the history no longer fits the context window. Current agents shrink this history by having a model summarize it, so each compaction rereads and rewrites the history it replaces, and cache-aware triggers decide when to compact while taking the size of the result as given. We present Folio, a context manager that records, folds, and recovers history through one set of handles. While the agent runs, Folio records three linked levels: a short turn note the model writes as part of its ordinary reply (L1), an event manifest of every call written by the runtime (L2), and the captured source records (L3). Because these views already exist, the runtime folds the context programmatically, selecting coarser views for older turns. The fold prints the handles that index L2 and L3, so recovery tools that read bounded pages, compute over full text in files, and keep findings in a persistent dossier reach the evidence the agent needs with little added input. The fold trigger prices an explicit landing point that includes the retained budget. On 75 LOCA-bench tasks with DeepSeek-V4-Pro behind every system, Folio solves 66 tasks against 54 for the same runtime with model-written compaction and 49-59 for Claude Code, Codex, and SoL-Pi, in about half their working time, at 2.4 times lower cost than that runtime; each fold takes a median of 0.6 seconds.
Comments: 13 pages, 6 figures, 5 tables
Subjects: Artificial Intelligence (cs.AI)
Cite as: arXiv:2611.16627 [cs.AI]
  (or arXiv:2611.16627v1 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2611.16627

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Yubo Ruan [view email]
[v1] Thu, 12 Nov 2026 10:59:40 UTC (563 KB)

来源:arXiv cs.AI · arxiv.org