MemGuard: Persisting Verifier Signals for LLM-Agent Memory Governance

📅 2026-08-22
📈 Citations: 0
Influential: 0
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🤖 AI Summary
为解决LLM代理在长期任务中因不可靠准入和记忆漂移导致的记忆问题,MemGuard通过将验证信号转化为持久元数据来优化记忆管理。
📝 Abstract
LLM agents are moving from single-prompt use to long task streams in which reusable memory becomes a core capability for terminal, software-engineering, and web tasks. Such memory is useful only when stored experience remains reliable across hundreds of interactions, but two failure modes break that assumption in practice. The first is unreliable admission: failed trajectories,accidental successes, and misleading observations enter memory because they appear relevant, then mislead later decisions. The second is memory drift: long-running banks accumulate duplicate, stale, and conflicting records that retrieval alone cannot repair. MemGuard's key distinction is to treat verifier output not as a one-shot filter, but as persistent lifecycle metadata. It converts multi-criteria score-token verification into reward, confidence, label, and uncertainty descriptors that are attached to every candidate before activation and reused during retrieval, conflict resolution, summarization, and archival. We evaluate MemGuard on Terminal-Bench 2.0, SWE-Bench Verified, WebArena, and Mind2Web across four backbones, comparing against four memory baselines plus a verifier-only control under matched runtime budgets. Averaged over five seeds, MemGuard achieves the best success metric and lowest average steps in all 16 backbone-benchmark settings, improving over ReasoningBank, the strongest prior baseline among the memory methods we evaluate, with a largest gain of 7.9 success-rate points on WebArena, 5.6 step-success-rate points on Mind2Web, and 2.4-3.5 points on terminal and software-engineering benchmarks. Code is available at https://github.com/whyyyyy123/MemGuard.
Problem

Research questions and friction points this paper is trying to address.

LLM agents
memory governance
unreliable admission
memory drift
Innovation

Methods, ideas, or system contributions that make the work stand out.

persistent lifecycle metadata
multi-criteria score-token verification
memory governance
verifier signals
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