29 lines
1.3 KiB
Markdown
29 lines
1.3 KiB
Markdown
 
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# Agent Memory Staleness: How Recency-Aware Ranking Fixes Retrieval Drift (Mem0)
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## Metadata
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| Field | Value |
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| Institute | Molodetz Institute — Research & Retrieval Division |
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| Subject | agent-memory-recency-tracking |
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| Document type | Source Citation Card |
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| Tier | 2 |
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| Source title | Agent Memory Staleness: How Recency-Aware Ranking Fixes Retrieval Drift |
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| Source URL | https://mem0.ai/library/context-engineering/memory-decay-for-long-running-agents-how-recency-aware-ranking-fixes-retrieval-staleness |
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| Source type | blog post / vendor docs |
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| Date researched | 2026-10-09 |
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| Researched by | tai (agent), model: Claude Sonnet 5, on behalf of retoor |
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| Research method | Search aggregator result listing (not independently opened or quoted) |
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| Confidence | Not independently verified |
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| Status | Active |
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## Why it's here
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Surfaced by the search "Mem0 memory scoring decay forgetting curve AI agent long term memory" as a context-engineering-focused Mem0 library article specifically about recency-aware ranking and retrieval staleness — closely related to the decay mechanism covered at Tier 1 in `mem0-introducing-memory-decay.md`, but this specific article was not independently opened during this pass.
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## Changelog
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| Date | Change |
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| 2026-10-09 | Logged as consulted-but-not-analyzed. |
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