Instruction-Tuned vs. Base Models on LawBench: Scaling Trends Beyond 30B Parameters

This report synthesises findings from 14 peer-reviewed papers addressing the following research question: Does the performance gap between base pre-trained models and instruction-tuned models on LawBench narrow as model capacity increases beyond 30B parameters. 9 claims were extracted from source literature; 9 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: Does the performance gap between base pre-trained models and instruction-tuned models on LawBench narrow as model capacity increases beyond 30B parameters?

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