ClawVM: 用于状态ful工具使用的LLM代理的抓取管理虚拟内存
ClawVM: Harness-Managed Virtual Memory for Stateful Tool-Using LLM Agents
AI总结：
ClawVM通过管理状态为类型化的页面，实现状态的可靠存储与回写，解决了状态丢失和回写失败的问题，提升了LLM代理的稳定性和可审计性。
摘要：
状态ful工具使用的LLM代理将上下文窗口视为工作内存，但当前的代理抓取管理驻留和持久化仅为尽力而为，导致反复失败：在压缩后丢失状态、重置时绕过回写、以及破坏性的回写。我们提出了ClawVM，一个虚拟内存层，通过最小保真不变式、基于令牌预算的多分辨率表示和在每个生命周期边界验证的回写来管理状态。由于抓取已经组装提示、调解工具和观察生命周期事件，因此将其置于此处是自然的强制执行点；将合同放置在此处使驻留和持久化成为确定性和可审计的。在合成工作负载、12个真实会话跟踪和对抗性压力测试中，ClawVM在最小保真集适合于令牌预算时消除了所有策略可控的故障，通过离线 oracle 验证，并且每个回合添加了中位数<50微秒的策略引擎开销。
英文摘要：
Stateful tool-using LLM agents treat the context window as working memory, yet today's agent harnesses manage residency and durability as best-effort, causing recurring failures: lost state after compaction, bypassed flushes on reset, and destructive writeback. We present \textsc{ClawVM}, a virtual memory layer that manages state as typed pages with minimum-fidelity invariants, multi-resolution representations under a token budget, and validated writeback at every lifecycle boundary. Because the harness already assembles prompts, mediates tools, and observes lifecycle events, it is the natural enforcement point; placing the contract there makes residency and durability deterministic and auditable. Across synthetic workloads, 12 real-session traces, and adversarial stress tests, \textsc{ClawVM} eliminates all policy-controllable faults whenever the minimum-fidelity set fits within the token budget, confirmed by an offline oracle, and adds median <50 microseconds of policy-engine overhead per turn.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
