tiered-memory-system-managed-by-model-itself-sustains CLM-0167mechanismsingle paperReviewed by AI and Russ Miller
A tiered memory system managed by the model itself sustains recall over conversations far longer than the context window.
Capability: Remembering across sessions
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- A tiered memory system managed by the model itself sustains recall over conversations far longer than the context window.
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Related claims
- Managing context explicitly, paging information in and out of a bounded window, sustains performance on tasks that exceed the window.Keeping its own context clean
- Recursively summarizing the dialogue into a running memory improves consistency in long conversations.Remembering across sessions
- Most models claiming long contexts fail well before their advertised length on synthetic retrieval, tracing and aggregation tasks.Losing information in long inputs
- For conversational long-term memory with 8-14B backbones and plain top-K dense retrieval, writing each dialogue span into several complementary low-overlap semantic views before indexing retrieves gold evidence for more queries than structured extraction into a single view, and the advantage is largest at small retrieval budgets.Remembering across sessions · reviewed by AI
- Holding the task fixed and only lengthening the input degrades reasoning long before the context limit is reached.Losing information in long inputs