Separate or shared encoders map both sides into a common space where related meaning should be nearby. An approximate nearest-neighbor index usually supplies candidates efficiently at scale.
Dense retrieval represents queries and documents as learned dense vectors and ranks them by vector similarity.
Separate or shared encoders map both sides into a common space where related meaning should be nearby. An approximate nearest-neighbor index usually supplies candidates efficiently at scale.