Model Size Effects on Self-Repair Efficiency in Llama-2 Code Generation

Abstract

Abstract: This report synthesises findings from 11 peer-reviewed papers addressing the following research question: To what extent does model size (e.g., 7B vs. 13B vs. 70B) impact the efficiency of self-repair in Llama-2 models, evaluated by the trade-off between pass@1 accuracy and inference latency in code. 0 claims were extracted from source literature; 0 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 6.8/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research Question

To what extent does model size (e.g., 7B vs. 13B vs. 70B) impact the efficiency of self-repair in Llama-2 models, evaluated by the trade-off between pass@1 accuracy and inference latency in code generation tasks?

Verification Level

Descriptive public verification status only; aggregate claim counts are public, but individual claim records are not exposed here.

Quality Tier

Descriptive public triage only; this tier does not alter current publication or DOI behavior.

Quality Dimensions

Automated triage signals derived from public fields; not human peer review or independent validation.

Correction Record

Public corrections are additive records. Current status does not claim the synthesis is error-free.

Provenance