Temporal Validity in Retrieval Memory: Eliminating Stale-Fact Errors for AI Agents over Evolving Knowledge
Deterministic supersession that RAG cannot match by construction
RAG gives agents access to accumulated knowledge but has no model of time. When a fact changes, cosine similarity surfaces both stale and current values nearly equally. The published study stores facts, then retires contradicted values with a deterministic supersession rule in a bi-temporal ledger. Results belong to the stated benchmarks and protocol, not to a product guarantee.
- Cosine AUROC 0.59 for contradiction versus duplicate
- Evolving knowledge accuracy 0.95 to 1.00 versus RAG 0.20 to 0.47 on the stated local benchmarks
- Forced-answer stale-fact error near 0 versus RAG 15 to 40 percent in that protocol