Michael Granitzer

Query Performance Prediction under Corpus Growth in Dense Retrieval

This work extends the QPP paradigm by studying query performance degradation under corpus inflation in dense retrieval systems and proposes simple adaptations to established QPP measures, most notably a top-k vs background Wasserstein distance measure, which yield more consistent associations with degradation and outperform their original counterparts.