Constructive Circuit Amplification: Improving Math Reasoning in LLMs via Targeted Sub-Network Updates
The authors find sparse "circuits" inside language models that drive math reasoning and selectively strengthen only those pieces. They report up to 11.4% accuracy gains while touching about 1.6% of model components, keeping other skills like MMLU almost unchanged. ([ar5iv.org](https://ar5iv.org/abs/2512.16914))
Nikhil Prakash, Donghao Ren