Scientific and General Reasoning on MMLU Pro
68.08Pass@1MulFeRL
Evaluation Results
| Method | Links | |
|---|---|---|
| MulFeRLBackbone=Qwen3-4B-Inst, Training Strategy=Multi-turn Feedback-guided Reinforcement Learning2026.01 | 68.08 | |
| Critique-GRPOBackbone=Qwen3-4B-Inst, Training Strategy=Reinforcement Learning-based Finetuning2026.01 | 64.67 | |
| Dr.GRPOBackbone=Qwen3-4B-Inst, Training Strategy=Reinforcement Learning-based Finetuning2026.01 | 63.33 | |
| GRPOBackbone=Qwen3-4B-Inst, Training Strategy=Reinforcement Learning-based Finetuning2026.01 | 62.18 | |
| SFTBackbone=Qwen3-4B-Inst, Training Strategy=Supervised Learning-based Finetuning2026.01 | 60.46 | |
| CITL-FTBackbone=Qwen3-4B-Inst, Training Strategy=Supervised Learning-based Finetuning2026.01 | 60.18 | |
| RAFTBackbone=Qwen3-4B-Inst, Training Strategy=Supervised Learning-based Finetuning2026.01 | 59.53 | |
| Qwen3-4B-InstBackbone=Qwen3-4B-Inst, Training Strategy=Base Model2026.01 | 58.56 | |
| MulFeRLBackbone=Qwen2.5-7B-Base, Training Strategy=Multi-turn Feedback-guided Reinforcement Learning2026.01 | 54.89 | |
| Critique-GRPOBackbone=Qwen2.5-7B-Base, Training Strategy=Reinforcement Learning-based Finetuning2026.01 | 52.34 | |
| Dr.GRPOBackbone=Qwen2.5-7B-Base, Training Strategy=Reinforcement Learning-based Finetuning2026.01 | 51.88 | |
| GRPOBackbone=Qwen2.5-7B-Base, Training Strategy=Reinforcement Learning-based Finetuning2026.01 | 51.1 | |
| CITL-FTBackbone=Qwen2.5-7B-Base, Training Strategy=Supervised Learning-based Finetuning2026.01 | 47.86 | |
| SFTBackbone=Qwen2.5-7B-Base, Training Strategy=Supervised Learning-based Finetuning2026.01 | 47.2 | |
| RAFTBackbone=Qwen2.5-7B-Base, Training Strategy=Supervised Learning-based Finetuning2026.01 | 46.06 | |
| Qwen2.5-7B-BaseBackbone=Qwen2.5-7B-Base, Training Strategy=Base Model2026.01 | 45.06 | |
| Critique-GRPOTraining Data Volume=4k, Critique Mode=CoT-Critique2025.06 | 43.79 | |
| Oat-ZeroTraining Data Volume=46k2025.06 | 41.7 | |
| Qwen2.5-Math-7B-BaseTraining Data Volume=None2025.06 | 39.7 | |
| SimpleRL-ZeroTraining Data Volume=46k2025.06 | 34.5 | |
| PRIME-ZeroTraining Data Volume=46k2025.06 | 32.7 |