Retention Consequence in Lifecycle Memory Control
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Abstract (arXiv)
Persistent memory can fail after successful admission: a premise is written, then becomes a silent assumption, and later maintenance treats it as ordinary residue to be compressed, demoted, or evicted. We study this post-admission failure as a lifecycle-control problem. Existing memory systems already perform admission, update, compression, retrieval, and eviction. Our claim is not that such systems lack maintenance, but that retention consequence is often operationalized only indirectly through validity, similarity, recency, frequency, importance, or summarization signals rather than exposed as a separate lifecycle state. We therefore treat confidence as carried-forward validity/support evidence, and introduce strength as an explicit lifecycle state for retention consequence. We operationalize this distinction in StageMem, a small staged controller whose transient, working, and durable stores expose promotion, compression, and eviction pressure points. Across controlled premise-realization, compression, pressure, and implicit-heuristic diagnostics, the experiments separate writing too little, retaining the wrong high-cue content, forgetting costly premises, and preserving everything by saturation. Explicit retention consequence, used through lifecycle settlement, provides a control surface between omission and hoarding. For the targeted post-admission failure mode, the results support a lifecycle view of persistent memory: reliability depends not only on what enters memory, but on whether admission validity and retention consequence remain available during maintenance.
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References · 10
- 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,064
- 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,383
- 2023MemGPT: Towards LLMs as Operating Systemscited by 1,295
- 2025A-MEM: Agentic Memory for LLM Agentscited by 1,000
- 2024Evaluating Very Long-Term Conversational Memory of LLM Agentscited by 800
- 2024LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memorycited by 656
- 2023LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compressioncited by 443
- 2025Hierarchical Memory for High-Efficiency Long-Term Reasoning in LLM Agentscited by 60
- 2026AtomMem : Learnable Dynamic Agentic Memory with Atomic Memory Operationcited by 13
- 2026All-Mem: Agentic Lifelong Memory via Dynamic Topology Evolutioncited by 8
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