Adversarial Code Complexity and Inference Latency in DeepSeek R1 for HumanEval Tasks

Abstract

Abstract: This report synthesises findings from 13 peer-reviewed papers addressing the following research question: What is the relationship between adversarial code complexity (measured by cyclomatic complexity) and the inference latency of Deepseek R1 when generating solutions for HumanEval, and can efficiency. 11 claims were extracted from source literature; 5 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 5.7/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research Question

What is the relationship between adversarial code complexity (measured by cyclomatic complexity) and the inference latency of Deepseek R1 when generating solutions for HumanEval, and can efficiency improvements reduce the accuracy drop-off for high-complexity prompts?

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