# Paper: Infini Memory: Maintainable Topic Documents for Long-Term LLM Agent Memory

---
type: paper
title: "Infini Memory: Maintainable Topic Documents for Long-Term LLM Agent Memory"
authors: Suozhao Ji, Baodong Wu, Zehao Wang, Lei Xia, Qingping Li, Ruisong Wang, Wenbo Ding, Zhenhua Zhu, et al.
year: 2026
venue: arXiv
url: https://arxiv.org/abs/2606.10677
code_url:
source: arxiv
collected_at: 2026-07-08
published_at: 2026-06-09
updated_at: 2026-06-09
status: skimmed
relevance: high
topics:
  - agent-evaluation
  - memory
  - rag
  - tool-use
methods:
  - topic-documents
  - buffered-consolidation
  - agentic-retrieval
benchmarks:
  - MemoryAgentBench
  - LongMemEval
models:
  -
datasets:
  - cs.AI
  - cs.CL
related_concepts:
  - semantic-memory
  - selective-forgetting
related_jobs:
  -
related_experiments:
  - KC-001-agent-memory-pilot
related_projects:
  - learning/agent-memory
collection_score: 18
collection_queries: agent-memory
---

## One-line Takeaway

长期事实应被维护为带证据和时间的主题文档，并允许 Agent 多步检查，而不是只保存孤立记录和一次检索结果。

## Pilot Skim

- problem: 孤立记录难以聚合证据、修订事实和维护跨 session 一致性。
- method: observation 先进入 buffer，再巩固到 topic documents；读取时迭代 search、grep 和 read_lines。
- evidence: MemoryAgentBench overall 64.7；LongMemEval 上 summary-only 41.7、summary+BM25 76.0、agentic 79.3。
- boundary: multi-hop selective forgetting 仍困难；多步 retrieval 和周期维护增加计算成本。

## Used In

- [Agent Memory evidence matrix](../../learning/agent-memory/evidence-matrix.md)

## Links

- arXiv: https://arxiv.org/abs/2606.10677