Distilled vs. Full BERT Throughput in Large-Scale Pairwise Similarity Scoring

This report synthesises findings from 14 peer-reviewed papers addressing the following research question: How does the throughput of distilled sentence embedding models compare to full BERT architectures when performing pairwise similarity scoring on large-scale technical corpora. 8 claims were extracted from source literature; 8 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 8.7/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research goal: How does the throughput of distilled sentence embedding models compare to full BERT architectures when performing pairwise similarity scoring on large-scale technical corpora?

Autonomous literature synthesis. Automated review score: 8.7/10. Full text and citation available at Assignee Research.