Can LLMs Learn to Reason Robustly under Noisy Supervision?

Benchmark Model Rank Results
mathematical-reasoning-on-minerva-mathQwen3-4B-Base (with OLR)#17Accuracy: 44.9
mathematical-reasoning-on-olympiadbenchQwen3-4B-Base (with OLR)#28Accuracy: 48.9
mathematical-reasoning-on-math-500Qwen3-4B-Base (with OLR)#70Accuracy: 85.2
multi-task-language-understanding-on-mmlu-proQwen3-4B-Base (with OLR)#95Accuracy: 60.6
mathematical-reasoning-on-aime24Qwen3-4B-Base (with OLR)#111Acc: 23.8
mathematical-reasoning-on-aime-2025Qwen3-4B-Base (with OLR)#126Accuracy: 20.8