agent/papers/items/2026-2606-24595-memprobe-probing-long-term-agent-memory-via-hidden-user-state-recovery.md

Paper: MEMPROBE: Probing Long-Term Agent Memory via Hidden User-State Recovery

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type: paper title: "MEMPROBE: Probing Long-Term Agent Memory via Hidden User-State Recovery" authors: Enze Ma, Yufan Zhou, Wei-Chieh Huang, Jie Yang, Huanhuan Ma, Zixuan Wang, Chengze Li, Chunyu Miao, et al. year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.24595 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-23 updated_at: 2026-06-23 status: queued relevance: high topics:

• agent-evaluation
• memory
• rag
• tool-use methods:

benchmarks:

models:

datasets:

• cs.CL related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 16 collection_queries: agent-memory

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: agent-memory
• inferred topics: agent-evaluation, memory, rag, tool-use
• arXiv categories: cs.CL
• collection score: 16

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2606.24595