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EvoR Computational Overhead Scaling in Retrieval-Augmented Code Generation

Authors: Assignee Research;

EvoR Computational Overhead Scaling in Retrieval-Augmented Code Generation

Abstract

This report synthesises findings from 3 peer-reviewed papers addressing the following research question: How does the computational overhead of EVOR's synchronous query and knowledge base evolution scale with model size (e.g., 7B vs 34B parameters) on the MBPP benchmark when measured in tokens processed. 7 claims were extracted from source literature; 7 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 8.8/10. This report is a machine-generated literature synthesis and does not constitute original research.Research goal: How does the computational overhead of EVOR's synchronous query and knowledge base evolution scale with model size (e.g., 7B vs 34B parameters) on the MBPP benchmark when measured in tokens processed per second?Autonomous literature synthesis. Automated review score: 8.8/10. Full text and citation available at Assignee Research.

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