CAVE-Mem: Boundary-Aware Experience Validation for Memory Search
Long-term memory agents increasingly rely on it- erative search and reusable experience to answer questions over large personal, factual, or narrative histories. However, current experience-memory systems largely optimize relevance: they re- trieve past search lessons that appear similar to the current state and inject them into the prompt. A relevant experience can still be harmful when the memory substrate, question intent, answer granularity, or evidence boundary changes. We propose CAVE- Mem, a training-free framework that represents experience as a typed intervention operator with applicability, boundary, and utility conditions. CAVE-Mem first obtains a base memory-search answer, the...
| Authors | Xinyu Li |
|---|---|
| Primary category | cs.CL |
| Published | 23 September 2026 |
| Last updated at source | 23 September 2026 |
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