Synthetic vs. Human-Generated Math Data for Zero-Shot Benchmark Fine-Tuning - Assignee Research (Assignee Research, 2026)
This report synthesises findings from 13 peer-reviewed papers addressing the following research question: How does fine-tuning with synthetic math problems generated by a stronger model affect the zero-shot performance on the MATH and GSM8K benchmarks compared to human-written fine-tuning data. 0 claims were extracted from source literature; 0 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 3.0/10. This report is a machi
Machine-generated literature synthesis.