Accuracy on ARC Challenge (Reasoning)
0.946Accuracy (ARC)GRPO
Evaluation Results
| Method | Links | |
|---|---|---|
| GRPOBase Model=Qwen3-4B2025.10 | 0.946 | |
| SCOPE-RLBase Model=Qwen3-4B2025.10 | 0.943 | |
| Entropy-RegBase Model=Qwen3-4B2025.10 | 0.939 | |
| Entropy-AdvBase Model=Qwen3-4B2025.10 | 0.936 | |
| KL-covBase Model=Qwen3-4B2025.10 | 0.933 | |
| BaseBase Model=Qwen3-4B2025.10 | 0.929 | |
| DAPOBase Model=Qwen3-4B2025.10 | 0.926 | |
| CISPOBase Model=Qwen3-4B2025.10 | 0.923 | |
| QwenCheckpoint=SFTMaxOOD2025.09 | 0.92 | |
| SCOPE-RLBase Model=Qwen2.5-7B2025.10 | 0.916 | |
| DAPOBase Model=Qwen2.5-7B2025.10 | 0.909 | |
| KL-covBase Model=Qwen2.5-7B2025.10 | 0.909 | |
| Entropy-AdvBase Model=Qwen2.5-7B2025.10 | 0.906 | |
| CISPOBase Model=Qwen2.5-7B2025.10 | 0.899 | |
| Entropy-RegBase Model=Qwen2.5-7B2025.10 | 0.896 | |
| GRPOBase Model=Qwen2.5-7B2025.10 | 0.893 | |
| QwenCheckpoint=SFTEnd2025.09 | 0.88 | |
| QwenCheckpoint=RLEnd2025.09 | 0.88 | |
| BaseBase Model=Qwen2.5-7B2025.10 | 0.863 | |
| DAPOBase Model=Qwen2.5-Math-7B2025.10 | 0.809 | |
| CISPOBase Model=Qwen2.5-Math-7B2025.10 | 0.809 | |
| SCOPE-RLBase Model=Qwen2.5-Math-7B2025.10 | 0.809 | |
| Entropy-AdvBase Model=Qwen2.5-Math-7B2025.10 | 0.803 | |
| LLaMACheckpoint=SFTMaxOOD2025.09 | 0.8 | |
| LLaMACheckpoint=RLEnd2025.09 | 0.8 | |
| KL-covBase Model=Qwen2.5-Math-7B2025.10 | 0.799 | |
| Entropy-RegBase Model=Qwen2.5-Math-7B2025.10 | 0.796 | |
| GRPOBase Model=Qwen2.5-Math-7B2025.10 | 0.789 | |
| LLaMACheckpoint=SFTEnd2025.09 | 0.7 | |
| BaseBase Model=Qwen2.5-Math-7B2025.10 | 0.699 | |
| BF16-BaselineEff. Bits=16, Model=Qwen3-8B2026.06 | 0.5657 | |
| GRINQH-6b-RTNEff. Bits=3.05, Model=Qwen3-8B2026.06 | 0.5614 | |
| BF16-BaselineEff. Bits=16, Model=Llama-3.1-8B-Instruct2026.06 | 0.5589 | |
| GRINQH-8b-RTNEff. Bits=3.96, Model=Llama-3.1-8B-Instruct2026.06 | 0.558 | |
| GRINQH-4b-GPTQEff. Bits=3.02, Model=Qwen3-8B2026.06 | 0.552 | |
| GRINQH-8b-RTNEff. Bits=3.06, Model=Qwen3-8B2026.06 | 0.5512 | |
| GRINQH-8b-RTNEff. Bits=2.95, Model=Llama-3.1-8B-Instruct2026.06 | 0.5503 | |
| GRINQH-4b-GPTQEff. Bits=3.01, Model=Llama-3.1-8B-Instruct2026.06 | 0.5427 | |
| MatGPTQ-EP-Mix’n’MatchEff. Bits=4.00, Model=Llama-3.1-8B-Instruct2026.06 | 0.5384 | |
| GRINQH-6b-RTNEff. Bits=2.98, Model=Llama-3.1-8B-Instruct2026.06 | 0.5358 | |
| GRINQH-8b-RTNEff. Bits=2.24, Model=Qwen3-8B2026.06 | 0.5299 | |
| GRINQH-6b-RTNEff. Bits=3.881, Model=Llama-3.1-8B-Instruct2026.06 | 0.529 | |
| MatGPTQEff. Bits=4.00, Model=Llama-3.1-8B-Instruct2026.06 | 0.5282 | |
| GRINQH-4b-GPTQEff. Bits=2.09, Model=Qwen3-8B2026.06 | 0.5171 | |
| MatGPTQEff. Bits=3.00, Model=Qwen3-8B2026.06 | 0.4872 | |
| MatGPTQ-EP-Mix’n’MatchEff. Bits=3.00, Model=Llama-3.1-8B-Instruct2026.06 | 0.4753 | |
| MatGPTQ-EP-Mix’n’MatchEff. Bits=3.00, Model=Qwen3-8B2026.06 | 0.4753 | |
| YOCO (CLSA)Model Scale=4B, Attention=Cross-Layer Sparse2026.06 | 0.465 | |
| MatGPTQEff. Bits=3.00, Model=Llama-3.1-8B-Instruct2026.06 | 0.4625 | |
| YOCO (Dense)Model Scale=4B2026.06 | 0.461 | |
| GRINQH-8b-RTNEff. Bits=2.08, Model=Llama-3.1-8B-Instruct2026.06 | 0.4608 | |
| TransformerModel Scale=4B2026.06 | 0.453 | |
| BaselineCompression Ratio=0.02026.05 | 0.38 | |
| SAES-SVD + PARSECompression Ratio=0.22026.05 | 0.37 | |
| SAES-SVD + PARSECompression Ratio=0.42026.05 | 0.31 | |
| SAES-SVD + PARSECompression Ratio=0.62026.05 | 0.31 |