Geodesic Distance Retrieval vs. Cosine Similarity in Large-Scale Language Model Inference

This report synthesises findings from 14 peer-reviewed papers addressing the following research question: What is the impact of geodesic distance-based retrieval on inference latency and throughput compared to cosine similarity in large-scale language model applications. 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: What is the impact of geodesic distance-based retrieval on inference latency and throughput compared to cosine similarity in large-scale language model applications?

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