Query expansion and re ranking can and often do coexist
Roughly, first there is the query analysis/manipulation phase where you might have NER, spell check, query expansion/relaxation etc
Then there is the selection phase, where you retrieve all items that are relevant. Sometimes people will bring in results from both text and vector based indices. Perhaps and additional layer to group results
Then finally you have the reranking layer using a cross encoder model which might even have some personalisation in the mix
Also, with vector search you might not need query expansion necessarily since semantic similarity does loose association. But every domain is unique and there’s only one way to find out
