Unverified50% confidenceFactExact time
The core mechanism of vector search is nearest-neighbor search: as long as the vector store is non-empty, it will always return a result, and there is no built-in "no result" branch.
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10/28/2026
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UnverifiedSemantic retrieval (vector search over stored knowledge) and state recovery (loading a checkpointed workflow) solve different problems; vector search can surface relevant context, but should never be the sole mechanism for restoring the exact state of an in-progress task.71% similarUnverifiedWhen an embedding column is partially regenerated, the vector database's nearest-neighbor search does not report an error; the only symptom is a slow decline in retrieval quality, which looks like model drift or data quality rot.71% similarUnverified在限定深度的搜索中，价值函数本质上是在近似它下方的整棵搜索树70% similarUnverifiedThe failure of greedy search is traced back to the non-monotonicity of the invariance statistic along univariate paths70% similarUnverifiedThe pragmatic approach is to first evaluate retrieval quality independently before connecting the generation stage: if the Top-K retrieved content does not contain the answer, switching to a stronger model cannot remedy the situation.67% similar
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