The Same Question, Completely Different Results

Vector retrieval has a fragility that's easy to overlook: rephrase the same question, and the results can change dramatically.

"How does the BGE model perform on Chinese text?" and "Which embedding is recommended for Chinese?" are semantically near-identical — but their embedding vectors sit at different positions in high-dimensional space, often returning different document sets entirely.

This is a structural property of Bi-Encoders: query and document are each encoded without knowing the other exists, making the result sensitive to subtle phrasing differences.

Previous articles optimized the document side — better chunking strategies help documents get found.…