  Dense retrieval has made significant advancements in information retrieval
(IR) by achieving high levels of effectiveness while maintaining online
efficiency during a single-pass retrieval process. However, the application of
pseudo relevance feedback (PRF) to further enhance retrieval effectiveness
results in a doubling of online latency. To address this challenge, this paper
presents a single-pass dense retrieval framework that shifts the PRF process
offline through the utilization of pre-generated pseudo-queries. As a result,
online retrieval is reduced to a single matching with the pseudo-queries, hence
providing faster online retrieval. The effectiveness of the proposed approach
is evaluated on the standard TREC DL and HARD datasets, and the results
demonstrate its promise. Our code is openly available at
https://github.com/Rosenberg37/OPRF.

Information Retrieval