Sliding Window Attention Degradation in Mistral 7B on LongCodeEval Beyond 32k Tokens

This report synthesises findings from 7 peer-reviewed papers addressing the following research question: How does the accuracy of Mistral 7B with sliding window attention degrade on the LongCodeEval benchmark compared to full attention baselines when context length exceeds 32k tokens. 8 claims were extracted from source literature; 6 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 7.5/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research goal: How does the accuracy of Mistral 7B with sliding window attention degrade on the LongCodeEval benchmark compared to full attention baselines when context length exceeds 32k tokens?

Autonomous literature synthesis. Automated review score: 7.5/10. Full text and citation available at Assignee Research.