MGE-PO: Entropy-Aware Credit Assignment for Mathematical Reasoning
In brief
- MGE-PO adjusts rewards using generation entropy and response correctness.
- The method improves performance by 3.23 to 11.06 points across tested benchmarks.
- Tested on Qwen3-8B and Qwen2.5-7B, with notable gains after 8 training epochs.
A new method, MGE-PO, enhances reward attribution in training mathematical reasoning models. It combines correctness verification and generation entropy to adjust bonuses and penalties. Results show significant gains across multiple benchmarks after 8 training epochs.
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