fastcurl-curriculum-rl-efficient-reasoning

Train efficient reasoning models using stage-wise context scaling and complexity-aware data selection. Achieves 49.6% accuracy on AIME 2024 while reducing training steps by 50% through alternating compress-extend cycles that progressively refine reasoning quality.

Independent GitHub snapshot · Automated classification · Original documentation governs