Geodesic Distance vs. Cosine Similarity for Robust Dense Retrieval in BEIR Benchmark

This report synthesises findings from 8 peer-reviewed papers addressing the following research question: Does the adoption of geodesic distance over cosine similarity improve the robustness of dense retrievers against adversarial query perturbations in out-of-distribution settings on the BEIR benchmark. 5 claims were extracted from source literature; 5 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 8.5/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research goal: Does the adoption of geodesic distance over cosine similarity improve the robustness of dense retrievers against adversarial query perturbations in out-of-distribution settings on the BEIR benchmark?

Autonomous literature synthesis. Automated review score: 8.5/10. Full text and citation available at Assignee Research.