All-Mem: Agentic Lifelong Memory via Dynamic Topology Evolution
Lifelong interactive agents are expected to assist users over months or years, which requires continually writing long term memories while retrieving the right evidence for each new query under fixed context and latency budgets. Existing memory systems often degrade as histories grow, yielding redundant, outdated, or noisy retrieved contexts. We present \textbf{All-Mem}, an online/offline lifelong memory framework that maintains a topology structured memory bank via explicit, non destructive consolidation, avoiding the irreversible information loss typical of summarization based compression. In online operation, it anchors retrieval on a bounded visible surface to keep coarse search cost ...
| Authors | Can Lv, Heng Chang, Shengyu Tao et al. |
|---|---|
| Primary category | cs.IR |
| Published | 20 March 2026 |
| Last updated at source | 15 June 2026 |
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